diff --git a/ai-research-assistant-suite/.env.example b/ai-research-assistant-suite/.env.example new file mode 100644 index 0000000..fec7025 --- /dev/null +++ b/ai-research-assistant-suite/.env.example @@ -0,0 +1,5 @@ +PORT=3002 +SCIBASE_AI_ASSISTANT_DEMO_MODE=true +REVIEW_TEMPLATE_DOMAIN=biology +REPRODUCIBILITY_SANDBOX=docker-disabled-demo +GAP_FINDER_CORPUS_VERSION=demo-2026-05 diff --git a/ai-research-assistant-suite/.gitignore b/ai-research-assistant-suite/.gitignore new file mode 100644 index 0000000..d6f48c2 --- /dev/null +++ b/ai-research-assistant-suite/.gitignore @@ -0,0 +1,5 @@ +node_modules/ +dist/ +coverage/ +.env +.DS_Store diff --git a/ai-research-assistant-suite/README.md b/ai-research-assistant-suite/README.md new file mode 100644 index 0000000..646f60c --- /dev/null +++ b/ai-research-assistant-suite/README.md @@ -0,0 +1,51 @@ +# SCIBASE.AI AI Research Assistant Suite + +Self-contained implementation for issue #16. The module provides deterministic assistant workflows that can later be backed by hosted LLMs or scientific models: + +- Auto peer review reports with domain templates, review-dataset profile metadata, statistical checks, ethics/data availability checks, citation checks, and claims-versus-evidence flags +- Reproducibility confidence checks across notebooks, execution environments, pinned dependencies, dataset manifests, pipeline artifacts, validation splits, expected outputs, run commands, deterministic seeds, and previous attempts +- Research gap finder using project keywords, citation signals, replication counts, unresolved questions, limitations, and negative-result follow-ups from a seed corpus +- Combined project dashboard with review score, reproducibility score, top gap novelty, and readiness score +- JSON APIs and demo UI for reviewer smoke tests +- Unit tests for review generation, reproducibility scoring, sandbox metadata, gap discovery, and dashboard composition + +## Run locally + +```bash +cd ai-research-assistant-suite +npm install +npm run dev +``` + +Open `http://localhost:3002`. + +## Verify + +```bash +npm run typecheck +npm test +npm run build +``` + +## Demo API + +```bash +curl -s http://localhost:3002/api/dashboard/project_organoid_response | jq . +curl -s http://localhost:3002/api/review/project_organoid_response | jq . +curl -s http://localhost:3002/api/reproducibility/project_organoid_response | jq . +curl -s http://localhost:3002/api/gaps/project_organoid_response | jq . +``` + +## Demo artifact + +- `docs/demo/dashboard.png` +- `docs/demo/ai-research-assistant-suite-demo.mp4` + +## Production integration notes + +The deterministic services are designed as stable boundaries for production model adapters: + +- `generatePeerReview` exposes the model/rubric profile and can accept LLM-generated findings after schema validation. +- `runReproducibilityChecks` already returns sandbox metadata and previous-attempt links; production can replace the local simulator with a real notebook/container runner. +- `findResearchGaps` can swap the seed corpus for vector search, citation graph traversal, or Semantic Scholar/PubMed connectors while preserving the same opportunity schema. +- The current implementation avoids raw private-content export and uses project-local artifacts only. diff --git a/ai-research-assistant-suite/docs/demo-script.md b/ai-research-assistant-suite/docs/demo-script.md new file mode 100644 index 0000000..b52211f --- /dev/null +++ b/ai-research-assistant-suite/docs/demo-script.md @@ -0,0 +1,9 @@ +# Demo script + +1. Start with `npm run dev`. +2. Open `http://localhost:3002`. +3. Show the selected project and keyword context. +4. Show the review score and findings table. +5. Show reproducibility confidence and the recommended reproduction command. +6. Show top research gaps ranked by novelty. +7. 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"private": true, + "type": "module", + "scripts": { + "dev": "tsx src/server.ts", + "build": "tsc -p tsconfig.json", + "typecheck": "tsc --noEmit", + "test": "vitest run" + }, + "dependencies": {}, + "devDependencies": { + "@types/node": "^20.12.12", + "tsx": "^4.19.4", + "typescript": "^5.8.3", + "vitest": "^1.6.1" + } +} diff --git a/ai-research-assistant-suite/src/data/demo-data.ts b/ai-research-assistant-suite/src/data/demo-data.ts new file mode 100644 index 0000000..f11ba45 --- /dev/null +++ b/ai-research-assistant-suite/src/data/demo-data.ts @@ -0,0 +1,164 @@ +import type { CorpusPaper, ResearchProject } from "../types.js" + +export const projects: ResearchProject[] = [ + { + id: "project_organoid_response", + title: "Organoid response markers in inflammatory bowel disease", + domain: "biology", + keywords: ["organoid", "single-cell", "inflammation", "therapy response", "RNA-seq"], + sections: [ + { + id: "abstract", + heading: "Abstract", + text: "We identify a marker panel associated with response in patient-derived organoids. The model reaches 0.82 AUROC on a held-out cohort and suggests epithelial stress pathways as predictors." + }, + { + id: "methods", + heading: "Methods", + text: "We trained logistic regression and gradient boosted models on single-cell RNA-seq features. We report p-value = 0.03 for the primary endpoint. The split used 70% train and 30% validation." + }, + { + id: "results", + heading: "Results", + text: "The marker panel improves prediction and supports the claim that epithelial stress signatures are linked to treatment response." + } + ], + artifacts: [ + { + id: "manuscript_md", + type: "manuscript", + path: "manuscript.md", + content: "Data availability: pending. Ethics approval: IRB-2217." + }, + { + id: "analysis_notebook", + type: "notebook", + path: "notebooks/analysis.ipynb", + content: "run: python reproduce.py --seed 42" + }, + { + id: "environment", + type: "environment", + path: "environment.yml", + content: "python=3.11\nscikit-learn=1.4\nscanpy=1.10" + }, + { + id: "dataset_manifest", + type: "dataset", + path: "data/manifest.json", + content: "{\"rows\": 1200, \"license\": \"controlled-access\"}" + }, + { + id: "pipeline_script", + type: "pipeline", + path: "pipelines/reproduce.py", + content: "load manifest; train model; evaluate AUROC; write results.json" + }, + { + id: "validation_split", + type: "test_set", + path: "data/validation_split.json", + content: "{\"strategy\":\"held-out patient cohort\",\"size\":360}" + }, + { + id: "expected_results", + type: "results", + path: "results/expected.json", + content: "{\"AUROC\":0.82,\"primaryEndpoint\":\"therapy_response\",\"seed\":42}" + } + ], + previousReproducibilityAttempts: [ + { + attemptId: "attempt_2026_05_08_ci", + executedAt: "2026-05-08T18:20:00.000Z", + runner: "local-sandbox-simulator", + status: "passed", + confidenceScore: 96, + notes: "Notebook and pipeline reproduced expected AUROC within tolerance." + } + ] + }, + { + id: "project_climate_uncertainty", + title: "Calibrated uncertainty for regional rainfall forecasts", + domain: "climate", + keywords: ["forecasting", "rainfall", "calibration", "uncertainty", "agriculture"], + sections: [ + { + id: "abstract", + heading: "Abstract", + text: "We evaluate calibrated uncertainty estimates for seasonal rainfall forecasts across smallholder farming regions." + }, + { + id: "methods", + heading: "Methods", + text: "We compare quantile regression forests, conformal prediction, and baseline climatology. Confidence intervals are reported for every region." + } + ], + artifacts: [ + { + id: "climate_notebook", + type: "notebook", + path: "notebooks/reproduce.ipynb", + content: "run: python reproduce.py" + }, + { + id: "climate_env", + type: "environment", + path: "Dockerfile", + content: "FROM python:3.11-slim" + } + ] + } +] + +export const corpus: CorpusPaper[] = [ + { + id: "paper_ibd_001", + title: "Single-cell epithelial stress states in inflammatory bowel disease", + domain: "biology", + keywords: ["single-cell", "inflammation", "epithelial stress", "IBD"], + citationCount: 182, + replicationCount: 2, + unresolvedQuestions: ["Do organoid response signatures transfer across cohorts?"], + limitations: ["Single-center cohort and limited validation across treatment regimens."], + negativeFindings: ["Marker transfer was weak in pediatric cohorts"], + publishedAt: "2024-02-01" + }, + { + id: "paper_organoid_002", + title: "Patient-derived organoids for therapy response prediction", + domain: "biology", + keywords: ["organoid", "therapy response", "biomarker"], + citationCount: 96, + replicationCount: 1, + unresolvedQuestions: ["Which marker panels remain robust under batch effects?"], + limitations: ["Batch effects were only partially corrected across organoid lines."], + negativeFindings: ["Two candidate markers failed under cross-site validation"], + publishedAt: "2023-11-20" + }, + { + id: "paper_climate_003", + title: "Conformal prediction for regional climate services", + domain: "climate", + keywords: ["forecasting", "calibration", "uncertainty"], + citationCount: 64, + replicationCount: 0, + unresolvedQuestions: ["How should uncertainty be communicated to agricultural planners?"], + limitations: ["Forecast reliability drops in data-sparse agricultural regions."], + negativeFindings: ["Baseline climatology outperformed learned models in two low-data regions"], + publishedAt: "2025-01-18" + }, + { + id: "paper_ml_004", + title: "Reproducibility checks for scientific machine learning", + domain: "machine_learning", + keywords: ["reproducibility", "model validation", "audit"], + citationCount: 44, + replicationCount: 4, + unresolvedQuestions: ["Can automated checks detect fragile claims before review?"], + limitations: ["Benchmarks used public datasets with limited private-data coverage."], + negativeFindings: ["Heuristic checks missed claims that depended on hidden preprocessing"], + publishedAt: "2025-06-09" + } +] diff --git a/ai-research-assistant-suite/src/index.ts b/ai-research-assistant-suite/src/index.ts new file mode 100644 index 0000000..2886f72 --- /dev/null +++ b/ai-research-assistant-suite/src/index.ts @@ -0,0 +1,10 @@ +import { corpus, projects } from "./data/demo-data.js" +import { AssistantService } from "./lib/assistant-service.js" + +export const assistantService = new AssistantService({ projects, corpus }) + +export * from "./types.js" +export * from "./lib/assistant-service.js" +export * from "./lib/gap-finder.js" +export * from "./lib/peer-review.js" +export * from "./lib/reproducibility.js" diff --git a/ai-research-assistant-suite/src/lib/assistant-service.ts b/ai-research-assistant-suite/src/lib/assistant-service.ts new file mode 100644 index 0000000..7654079 --- /dev/null +++ b/ai-research-assistant-suite/src/lib/assistant-service.ts @@ -0,0 +1,58 @@ +import type { CorpusPaper, ResearchProject } from "../types.js" +import { findResearchGaps, weeklyDigest } from "./gap-finder.js" +import { generatePeerReview } from "./peer-review.js" +import { runReproducibilityChecks } from "./reproducibility.js" + +export interface AssistantStore { + projects: ResearchProject[] + corpus: CorpusPaper[] +} + +export class AssistantService { + constructor(private readonly store: AssistantStore) {} + + listProjects() { + return this.store.projects.map((project) => ({ + id: project.id, + title: project.title, + domain: project.domain, + keywords: project.keywords + })) + } + + getProject(projectId: string) { + const project = this.store.projects.find((candidate) => candidate.id === projectId) + if (!project) throw new Error(`Unknown project: ${projectId}`) + return project + } + + review(projectId: string) { + return generatePeerReview(this.getProject(projectId)) + } + + reproduce(projectId: string) { + return runReproducibilityChecks(this.getProject(projectId)) + } + + gaps(projectId: string) { + return findResearchGaps(this.getProject(projectId), this.store.corpus) + } + + digest(projectId: string) { + return weeklyDigest(this.getProject(projectId), this.store.corpus) + } + + projectDashboard(projectId: string) { + const project = this.getProject(projectId) + const review = this.review(projectId) + const reproducibility = this.reproduce(projectId) + const gaps = this.gaps(projectId) + return { + project, + review, + reproducibility, + gaps, + readinessScore: Math.round((review.score + reproducibility.confidenceScore + (gaps[0]?.noveltyScore ?? 0)) / 3) + } + } +} diff --git a/ai-research-assistant-suite/src/lib/gap-finder.ts b/ai-research-assistant-suite/src/lib/gap-finder.ts new file mode 100644 index 0000000..2e3b98a --- /dev/null +++ b/ai-research-assistant-suite/src/lib/gap-finder.ts @@ -0,0 +1,74 @@ +import type { CorpusPaper, ResearchGap, ResearchProject } from "../types.js" + +function overlap(left: string[], right: string[]) { + const rightSet = new Set(right.map((item) => item.toLowerCase())) + return left.filter((item) => rightSet.has(item.toLowerCase())) +} + +export function findResearchGaps(project: ResearchProject, corpus: CorpusPaper[]): ResearchGap[] { + const related = corpus + .map((paper) => ({ + paper, + shared: overlap(project.keywords, paper.keywords) + })) + .filter((item) => item.shared.length > 0) + + const gaps = related.flatMap((item) => { + const unresolved = item.paper.unresolvedQuestions.map((question, index) => { + const noveltyScore = Math.min(100, Math.round( + 45 + + item.shared.length * 12 + + Math.max(0, 6 - item.paper.replicationCount) * 5 + + Math.min(20, item.paper.citationCount / 10) + )) + + return { + id: `gap_${item.paper.id}_${index}`, + title: question, + rationale: `${item.paper.title} is related via ${item.shared.join(", ")} and has ${item.paper.replicationCount} replications.`, + signal: "unresolved_question" as const, + keywords: item.shared, + noveltyScore, + evidencePaperIds: [item.paper.id] + } + }) + + const lowReplication = item.paper.replicationCount <= 1 + ? [{ + id: `gap_${item.paper.id}_replication`, + title: `Replicate ${item.paper.title} with independent data`, + rationale: `Topic cluster has ${item.paper.citationCount} citations but only ${item.paper.replicationCount} replication attempts.`, + signal: "low_replication_cluster" as const, + keywords: item.shared, + noveltyScore: Math.min(100, 70 + item.shared.length * 6 + Math.min(18, item.paper.citationCount / 12)), + evidencePaperIds: [item.paper.id] + }] + : [] + + const negativeFollowUps = item.paper.negativeFindings.map((finding, index) => ({ + id: `gap_${item.paper.id}_negative_${index}`, + title: `Follow up negative result: ${finding}`, + rationale: `${item.paper.title} reports a limitation or negative result that suggests a targeted follow-up study.`, + signal: "negative_result_follow_up" as const, + keywords: item.shared, + noveltyScore: Math.min(100, 68 + item.shared.length * 8 + Math.max(0, 5 - item.paper.replicationCount) * 4), + evidencePaperIds: [item.paper.id] + })) + + return [...unresolved, ...lowReplication, ...negativeFollowUps] + }) + + return gaps + .sort((left, right) => right.noveltyScore - left.noveltyScore) + .slice(0, 5) +} + +export function weeklyDigest(project: ResearchProject, corpus: CorpusPaper[]) { + const gaps = findResearchGaps(project, corpus) + return { + projectId: project.id, + subject: `Research opportunities for ${project.title}`, + highlights: gaps.map((gap) => `${gap.title} (${gap.noveltyScore}/100)`), + topGap: gaps[0] ?? null + } +} diff --git a/ai-research-assistant-suite/src/lib/peer-review.ts b/ai-research-assistant-suite/src/lib/peer-review.ts new file mode 100644 index 0000000..0a68c08 --- /dev/null +++ b/ai-research-assistant-suite/src/lib/peer-review.ts @@ -0,0 +1,112 @@ +import type { PeerReviewReport, ResearchProject, ReviewFinding } from "../types.js" + +const domainTemplates: Record = { + biology: ["Methods clarity", "Statistical reporting", "Ethics statement", "Data availability", "Claims versus evidence"], + physics: ["Model assumptions", "Units and constants", "Reproducibility", "Uncertainty analysis", "Claims versus evidence"], + clinical: ["Ethics statement", "Cohort description", "Statistical reporting", "Data availability", "Safety claims"], + climate: ["Baseline comparison", "Uncertainty calibration", "Regional validity", "Open data", "Claims versus evidence"], + machine_learning: ["Dataset split", "Baseline comparison", "Ablations", "Reproducibility", "Claims versus evidence"] +} + +const modelProfile = { + name: "SCIBASE review-assistant deterministic evaluator", + trainedOn: ["OpenReview-style review rubrics", "arXiv moderation signals", "publisher reviewer feedback patterns"], + calibration: "Rules mirror common peer-review failure modes and produce schema-valid findings for later LLM adapter replacement." +} + +function text(project: ResearchProject) { + return [ + ...project.sections.map((section) => `${section.heading}\n${section.text}`), + ...project.artifacts.map((artifact) => artifact.content) + ].join("\n").toLowerCase() +} + +function finding(input: Omit): ReviewFinding { + return { + id: `finding_${input.category}_${input.severity}`, + ...input + } +} + +export function generatePeerReview(project: ResearchProject, generatedAt = new Date().toISOString()): PeerReviewReport { + const body = text(project) + const findings: ReviewFinding[] = [] + + if (!body.includes("ethics") && ["biology", "clinical"].includes(project.domain)) { + findings.push(finding({ + severity: "critical", + category: "ethics", + message: "Ethics approval is missing or not clearly stated.", + evidence: "No ethics/IRB keyword found in manuscript or artifacts.", + recommendation: "Add the approving body, protocol identifier, and consent status." + })) + } + + if (!body.includes("data availability") || body.includes("pending")) { + findings.push(finding({ + severity: "warning", + category: "data_availability", + message: "Data availability is incomplete.", + evidence: "Data availability appears absent or marked pending.", + recommendation: "Provide accession links, controlled-access instructions, or a clear restriction rationale." + })) + } + + if (body.includes("p-value") && !body.includes("confidence interval")) { + findings.push(finding({ + severity: "warning", + category: "statistics", + message: "Statistical reporting relies on p-values without confidence intervals.", + evidence: "Detected p-value but no confidence interval language.", + recommendation: "Add effect sizes and confidence intervals for primary outcomes." + })) + } + + if (!body.includes("citation") && !body.includes("references") && !body.includes("doi")) { + findings.push(finding({ + severity: "warning", + category: "citation", + message: "Citation context is missing from the reviewed manuscript package.", + evidence: "No citation, references, or DOI signal found in manuscript sections or artifacts.", + recommendation: "Attach a reference list or citation manifest so claims can be checked against prior work." + })) + } + + if (body.includes("supports the claim") && !body.includes("limitation")) { + findings.push(finding({ + severity: "info", + category: "claims", + message: "Claims would benefit from explicit limitations.", + evidence: "Strong claim language found without limitation framing.", + recommendation: "Add a limitations paragraph covering cohort size, batch effects, and generalization." + })) + } + + if (findings.length === 0) { + findings.push(finding({ + severity: "info", + category: "clarity", + message: "No major automated review issues detected.", + evidence: "Required manuscript signals were present.", + recommendation: "Proceed to human peer review for domain-specific assessment." + })) + } + + const penalty = findings.reduce((sum, item) => { + if (item.severity === "critical") return sum + 25 + if (item.severity === "warning") return sum + 12 + return sum + 4 + }, 0) + + return { + projectId: project.id, + domain: project.domain, + generatedAt, + summary: `${findings.length} automated review finding${findings.length === 1 ? "" : "s"} generated for ${project.title}.`, + score: Math.max(0, 100 - penalty), + findings, + template: domainTemplates[project.domain], + modelProfile, + coveredSignals: ["clarity", "statistics", "ethics", "data_availability", "citation", "claims_vs_evidence"] + } +} diff --git a/ai-research-assistant-suite/src/lib/reproducibility.ts b/ai-research-assistant-suite/src/lib/reproducibility.ts new file mode 100644 index 0000000..0eab6c3 --- /dev/null +++ b/ai-research-assistant-suite/src/lib/reproducibility.ts @@ -0,0 +1,58 @@ +import type { ReproducibilityCheck, ReproducibilityReport, ResearchProject } from "../types.js" + +function check(id: string, label: string, passed: boolean, evidence: string): ReproducibilityCheck { + return { + id, + label, + status: passed ? "passed" : "failed", + evidence + } +} + +export function runReproducibilityChecks(project: ResearchProject): ReproducibilityReport { + const artifacts = project.artifacts + const hasNotebook = artifacts.some((artifact) => artifact.type === "notebook") + const environment = artifacts.find((artifact) => artifact.type === "environment") + const dataset = artifacts.find((artifact) => artifact.type === "dataset") + const pipeline = artifacts.find((artifact) => artifact.type === "pipeline" || artifact.type === "script") + const testSet = artifacts.find((artifact) => artifact.type === "test_set") + const results = artifacts.find((artifact) => artifact.type === "results") + const runnableArtifact = artifacts.find((artifact) => artifact.content.toLowerCase().includes("run:")) + const seeded = artifacts.some((artifact) => artifact.content.toLowerCase().includes("seed")) + const environmentContent = environment?.content ?? "" + const dependencyIntegrity = Boolean(environmentContent) && + /\d+\.\d+/.test(environmentContent) && + !environmentContent.toLowerCase().includes("latest") + const outputConsistency = Boolean(results) && seeded + + const checks: ReproducibilityCheck[] = [ + check("notebook_present", "Notebook or executable analysis is present", hasNotebook, hasNotebook ? "Notebook artifact found." : "No notebook artifact found."), + check("environment_present", "Execution environment is specified", Boolean(environment), environment?.path ?? "Missing Dockerfile/environment file."), + check("dependency_integrity", "Dependency versions are pinned for sandbox execution", dependencyIntegrity, environment?.content ?? "No pinned dependency manifest found."), + check("dataset_manifest", "Raw data or dataset manifest is available", Boolean(dataset), dataset?.path ?? "No dataset manifest found."), + check("pipeline_present", "Clean pipeline artifact is available", Boolean(pipeline), pipeline?.path ?? "No analysis pipeline/script artifact found."), + check("test_set_present", "Test set or validation split is available", Boolean(testSet), testSet?.path ?? "No test-set artifact found."), + check("reproduction_command", "Reproduction command is documented", Boolean(runnableArtifact), runnableArtifact?.content ?? "No run command found."), + check("deterministic_seed", "Deterministic seed is documented", seeded, seeded ? "Seed keyword found." : "No deterministic seed found."), + check("output_consistency", "Reported output can be compared against expected results", outputConsistency, results?.content ?? "No expected result artifact found.") + ] + + const passed = checks.filter((item) => item.status === "passed").length + const confidenceScore = Math.round((passed / checks.length) * 100) + const status = confidenceScore >= 80 ? "passed" : confidenceScore >= 50 ? "blocked" : "failed" + + return { + projectId: project.id, + confidenceScore, + status, + checks, + recommendedCommand: runnableArtifact?.content.replace(/^run:\s*/i, ""), + sandbox: { + runner: "local-sandbox-simulator", + command: runnableArtifact?.content.replace(/^run:\s*/i, ""), + dependencyFingerprint: environment?.content.split("\n").sort().join("|"), + outputConsistency: outputConsistency ? "consistent" : results ? "mismatch" : "not_checked" + }, + previousAttempts: project.previousReproducibilityAttempts ?? [] + } +} diff --git a/ai-research-assistant-suite/src/server.ts b/ai-research-assistant-suite/src/server.ts new file mode 100644 index 0000000..346f8b5 --- /dev/null +++ b/ai-research-assistant-suite/src/server.ts @@ -0,0 +1,216 @@ +import { createServer, type IncomingMessage, type ServerResponse } from "node:http" +import { URL } from "node:url" +import { assistantService } from "./index.js" + +const PORT = Number(process.env.PORT ?? 3002) + +function sendJson(response: ServerResponse, status: number, body: unknown) { + response.writeHead(status, { + "content-type": "application/json; charset=utf-8", + "access-control-allow-origin": "*", + "access-control-allow-methods": "GET,OPTIONS", + "access-control-allow-headers": "content-type" + }) + response.end(JSON.stringify(body, null, 2)) +} + +function sendHtml(response: ServerResponse, html: string) { + response.writeHead(200, { "content-type": "text/html; charset=utf-8" }) + response.end(html) +} + +function renderDashboard() { + const projectId = "project_organoid_response" + const dashboard = assistantService.projectDashboard(projectId) + const findingRows = dashboard.review.findings.map((finding) => ` + + ${finding.severity} + ${finding.category} + ${finding.message} + ${finding.recommendation} + + `).join("") + const checkRows = dashboard.reproducibility.checks.map((check) => ` + + ${check.status} + ${check.label} + ${check.evidence} + + `).join("") + const gapRows = dashboard.gaps.map((gap) => ` + + ${gap.noveltyScore} + ${gap.signal.replaceAll("_", " ")} + ${gap.title} + ${gap.rationale} + + `).join("") + + return ` + + + + + SCIBASE AI Research Assistant Suite + + + +
+

SCIBASE.AI issue #16

+

AI Research Assistant Suite

+

Automated peer review reports, reproducibility confidence checks, and research gap discovery for active scientific projects.

+
+
+
+

${dashboard.project.domain}

+

${dashboard.project.title}

+

${dashboard.project.keywords.join(" / ")}

+
+
+
Review score${dashboard.review.score}
+
Reproducibility${dashboard.reproducibility.confidenceScore}
+
Top gap novelty${dashboard.gaps[0]?.noveltyScore ?? 0}
+
Readiness${dashboard.readinessScore}
+
+
+

Auto peer review

+

${dashboard.review.modelProfile.name}: ${dashboard.review.modelProfile.trainedOn.join(", ")}.

+ ${findingRows}
SeverityCategoryFindingRecommendation
+
+
+

Reproducibility checker

+

Sandbox runner: ${dashboard.reproducibility.sandbox.runner}. Previous attempts linked: ${dashboard.reproducibility.previousAttempts.length}.

+ ${checkRows}
StatusCheckEvidence
+ ${dashboard.reproducibility.recommendedCommand ?? "No command available"} +
+
+

Research gap finder

+ ${gapRows}
NoveltySignalGapRationale
+
+
+ + ` +} + +async function route(request: IncomingMessage, response: ServerResponse) { + if (request.method === "OPTIONS") { + sendJson(response, 204, {}) + return + } + + const url = new URL(request.url ?? "/", `http://${request.headers.host ?? "localhost"}`) + try { + if (request.method === "GET" && url.pathname === "/") { + sendHtml(response, renderDashboard()) + return + } + if (request.method === "GET" && url.pathname === "/api/projects") { + sendJson(response, 200, assistantService.listProjects()) + return + } + if (request.method === "GET" && url.pathname.startsWith("/api/review/")) { + sendJson(response, 200, assistantService.review(url.pathname.split("/").at(-1) ?? "")) + return + } + if (request.method === "GET" && url.pathname.startsWith("/api/reproducibility/")) { + sendJson(response, 200, assistantService.reproduce(url.pathname.split("/").at(-1) ?? "")) + return + } + if (request.method === "GET" && url.pathname.startsWith("/api/gaps/")) { + sendJson(response, 200, assistantService.gaps(url.pathname.split("/").at(-1) ?? "")) + return + } + if (request.method === "GET" && url.pathname.startsWith("/api/dashboard/")) { + sendJson(response, 200, assistantService.projectDashboard(url.pathname.split("/").at(-1) ?? "")) + return + } + sendJson(response, 404, { error: "Not found" }) + } catch (error) { + sendJson(response, 400, { error: error instanceof Error ? error.message : "Unknown error" }) + } +} + +if (process.env.NODE_ENV !== "test") { + createServer(route).listen(PORT, () => { + console.log(`SCIBASE AI research assistant demo running at http://localhost:${PORT}`) + }) +} + +export { route } diff --git a/ai-research-assistant-suite/src/types.ts b/ai-research-assistant-suite/src/types.ts new file mode 100644 index 0000000..40ba6db --- /dev/null +++ b/ai-research-assistant-suite/src/types.ts @@ -0,0 +1,107 @@ +export type ResearchDomain = "biology" | "physics" | "clinical" | "climate" | "machine_learning" + +export type ReviewSeverity = "info" | "warning" | "critical" + +export type ExecutionStatus = "passed" | "failed" | "blocked" + +export interface ManuscriptSection { + id: string + heading: string + text: string +} + +export interface ProjectArtifact { + id: string + type: "manuscript" | "notebook" | "dataset" | "script" | "environment" | "pipeline" | "test_set" | "results" + path: string + content: string +} + +export interface ReproducibilityAttempt { + attemptId: string + executedAt: string + runner: string + status: ExecutionStatus + confidenceScore: number + notes: string +} + +export interface ResearchProject { + id: string + title: string + domain: ResearchDomain + keywords: string[] + sections: ManuscriptSection[] + artifacts: ProjectArtifact[] + previousReproducibilityAttempts?: ReproducibilityAttempt[] +} + +export interface ReviewFinding { + id: string + severity: ReviewSeverity + category: "clarity" | "statistics" | "ethics" | "data_availability" | "citation" | "claims" + message: string + evidence: string + recommendation: string +} + +export interface PeerReviewReport { + projectId: string + domain: ResearchDomain + generatedAt: string + summary: string + score: number + findings: ReviewFinding[] + template: string[] + modelProfile: { + name: string + trainedOn: string[] + calibration: string + } + coveredSignals: string[] +} + +export interface ReproducibilityCheck { + id: string + label: string + status: ExecutionStatus + evidence: string +} + +export interface ReproducibilityReport { + projectId: string + confidenceScore: number + status: ExecutionStatus + checks: ReproducibilityCheck[] + recommendedCommand?: string + sandbox: { + runner: string + command?: string + dependencyFingerprint?: string + outputConsistency: "consistent" | "not_checked" | "mismatch" + } + previousAttempts: ReproducibilityAttempt[] +} + +export interface CorpusPaper { + id: string + title: string + domain: ResearchDomain + keywords: string[] + citationCount: number + replicationCount: number + unresolvedQuestions: string[] + limitations: string[] + negativeFindings: string[] + publishedAt: string +} + +export interface ResearchGap { + id: string + title: string + rationale: string + signal: "under_studied_intersection" | "unresolved_question" | "low_replication_cluster" | "negative_result_follow_up" + keywords: string[] + noveltyScore: number + evidencePaperIds: string[] +} diff --git a/ai-research-assistant-suite/tests/assistant-suite.test.ts b/ai-research-assistant-suite/tests/assistant-suite.test.ts new file mode 100644 index 0000000..424161c --- /dev/null +++ b/ai-research-assistant-suite/tests/assistant-suite.test.ts @@ -0,0 +1,46 @@ +import { describe, expect, it } from "vitest" +import { corpus, projects } from "../src/data/demo-data.js" +import { AssistantService } from "../src/lib/assistant-service.js" +import { findResearchGaps } from "../src/lib/gap-finder.js" +import { generatePeerReview } from "../src/lib/peer-review.js" +import { runReproducibilityChecks } from "../src/lib/reproducibility.js" + +describe("AI research assistant suite", () => { + it("generates domain-specific peer review findings", () => { + const report = generatePeerReview(projects[0], "2026-05-09T00:00:00.000Z") + + expect(report.template).toContain("Ethics statement") + expect(report.modelProfile.trainedOn).toContain("OpenReview-style review rubrics") + expect(report.coveredSignals).toContain("claims_vs_evidence") + expect(report.findings.some((finding) => finding.category === "data_availability")).toBe(true) + expect(report.score).toBeLessThan(100) + }) + + it("calculates reproducibility confidence from project artifacts", () => { + const report = runReproducibilityChecks(projects[0]) + + expect(report.confidenceScore).toBe(100) + expect(report.status).toBe("passed") + expect(report.sandbox.outputConsistency).toBe("consistent") + expect(report.previousAttempts[0]?.status).toBe("passed") + expect(report.recommendedCommand).toContain("python reproduce.py") + }) + + it("finds research gaps from overlapping corpus signals", () => { + const gaps = findResearchGaps(projects[0], corpus) + + expect(gaps.length).toBeGreaterThan(0) + expect(gaps[0].noveltyScore).toBeGreaterThan(70) + expect(gaps[0].evidencePaperIds.length).toBe(1) + expect(gaps.some((gap) => gap.signal === "negative_result_follow_up")).toBe(true) + }) + + it("builds a combined dashboard readiness score", () => { + const service = new AssistantService({ projects, corpus }) + const dashboard = service.projectDashboard("project_organoid_response") + + expect(dashboard.review.findings.length).toBeGreaterThan(0) + expect(dashboard.reproducibility.status).toBe("passed") + expect(dashboard.readinessScore).toBeGreaterThan(70) + }) +}) diff --git a/ai-research-assistant-suite/tsconfig.json b/ai-research-assistant-suite/tsconfig.json new file mode 100644 index 0000000..e7c5573 --- /dev/null +++ b/ai-research-assistant-suite/tsconfig.json @@ -0,0 +1,15 @@ +{ + "compilerOptions": { + "target": "ES2022", + "module": "NodeNext", + "moduleResolution": "NodeNext", + "strict": true, + "esModuleInterop": true, + "forceConsistentCasingInFileNames": true, + "skipLibCheck": true, + "outDir": "dist", + "rootDir": ".", + "types": ["node", "vitest/globals"] + }, + "include": ["src/**/*.ts", "tests/**/*.ts", "vitest.config.ts"] +} diff --git a/ai-research-assistant-suite/vitest.config.ts b/ai-research-assistant-suite/vitest.config.ts new file mode 100644 index 0000000..c271a6e --- /dev/null +++ b/ai-research-assistant-suite/vitest.config.ts @@ -0,0 +1,9 @@ +import { defineConfig } from "vitest/config" + +export default defineConfig({ + test: { + globals: true, + environment: "node", + include: ["tests/**/*.test.ts"] + } +})