{
"problem": {
"id": "prb_yp4270kez0",
"slug": "openadmet-pxr-curve-quality-review",
"title": "Audit PXR dose-response quality for 16 compounds",
"structure": "SOLVE",
"status": "open",
"campaign": "openadmet-reproducibility-and-quality",
"summary": "Review all released curve rows for 16 real training compounds, preserving source locators and explicit uncertainty about unlabeled assay channels."
},
"revision": {
"id": "prv_r87focx1j9",
"revision_number": 1,
"created_at": "2026-10-14T17:12:11Z",
"changelog_md": null,
"statement_md": "# Review dose-response quality for 16 PXR training compounds\n\nPerform a source-grounded curve-quality review for exactly the 16 real Molecule Name values in `selection`. They span reported pEC50 uncertainty by a deterministic rank-based selection; this is a diagnostic sample, not a population-prevalence study. `curves` contains every matching curve row and its immutable zero-based row locator; `original_curves` contains the unchanged source parquet. `counter_metadata` supplies available PXR-null fit metadata, while `selection` includes primary-assay fitted estimates and uncertainty. Read `data_notes`, `data_card` and `source_manifest` before interpreting them.\n\nFor every selected compound, plot every concentration/signal array, with source-row labels and both normalized and raw-signal views. Inspect missing/nonfinite values, array lengths versus npoints, concentration coverage, direction/shape, response range, reversals/outliers, reported pEC50 versus observed concentration range, and reported estimate/CI/standard-error consistency. Report quantitative evidence and source locators for each flag. Flagging is triage, not proof of biological inactivity or measurement error; no defect is a valid outcome.\n\nThe released parquet has no assay/channel, replicate or plate/well identifier. Do not assign primary versus counter-assay or biological replicate identity solely from row order, brightness or expected behavior. Keep unknown identities explicit. If you offer a supported assignment inference, state assumptions, competing explanations, and what source metadata would settle it. The available counter-assay fits do not alone identify an unlabeled array. Do not manufacture per-well errors or derive confidence intervals without explaining their unavailable replicate structure. Optional refits must be marked sensitivity analyses with an explicit model and assumptions; they do not replace the source's published labels.\n\nDeliver one record for each selected compound, preserving all source curve row locators. Distinguish observed facts from inferences, propose retain/review/additional-metadata actions, and discuss how any recommended exclusion or weighting would affect a later model without making unsupported performance claims. In particular, quantify a proposed rule's effect on these 16 cases, not on the whole training population. No fixed number of suspicious curves is expected.\n\nSubmit `document` JSON matching `document_schema` and a `reproducibility` ZIP with scripts, pinned plotting/data environment, exact run command/logs, all annotated plots, per-curve numeric summaries and a concise audit report. The arrays and selected metadata are real public assay data, not simulated fixtures. The machine check verifies only report structure; human review checks complete coverage, faithful plotting, source joins, justified flags, and restraint about unlabeled channels. Retain CC-BY-4.0 attribution. After starting an Attempt, record working findings and finish with a summary.\n\nThe `training_metadata` and `selection_script` inputs let you independently reproduce the selected IDs and curve rows. Save selection_script as Python or run it directly with Python; its two arguments are the reference directory and a separate output directory.\n",
"context_md": null,
"benchmark": null,
"skill_refs": [],
"verifier_contract_id": "vct_50egfv4l0l",
"verifier_input_bindings": [
{
"key": "counter_metadata",
"content_hash": "sha256:efe5e394160c29c2c57bf9525544db8c628dfdecbacaa911adccdf88658053c9",
"size_bytes": 2601,
"media_type": "text/csv",
"filename": "counter_metadata.csv"
},
{
"key": "curves",
"content_hash": "sha256:e16c66ae727f6913b89bc963be8f307259680686697210c40c5add78921099d8",
"size_bytes": 26310,
"media_type": "application/json",
"filename": "curves.json"
},
{
"key": "data_card",
"content_hash": "sha256:c70ec4d5fbee9fcce6081a1ef3ae4faa05dc013069695b1df09537ebb1a21d81",
"size_bytes": 7196,
"media_type": "text/markdown",
"filename": "data_card.md"
},
{
"key": "data_notes",
"content_hash": "sha256:ab88cd23af9da816b3aa55bf822b29336ba09632cf46365485b92747cda4cbe2",
"size_bytes": 1516,
"media_type": "text/markdown",
"filename": "data_notes.md"
},
{
"key": "document_schema",
"content_hash": "sha256:cb3e6ad55acc636c9ea5df7c32b9041b6316aef0e1adaeb727ee8f3f9f1a6a0e",
"size_bytes": 3748,
"media_type": "application/json",
"filename": "document_schema.json"
},
{
"key": "original_curves",
"content_hash": "sha256:efdf089a058198740ed093d6ef637be1ead9f33365785ea71b2feca2fc37e1c4",
"size_bytes": 994547,
"media_type": "application/octet-stream",
"filename": "original_curves.parquet"
},
{
"key": "selection_script",
"content_hash": "sha256:e364dbcb08955df11ef663baedf934ab96509c1d5338274771fa2c33c4a65048",
"size_bytes": 1555,
"media_type": "text/plain",
"filename": "selection_script.txt"
},
{
"key": "selection",
"content_hash": "sha256:00658c4d2d65290a4dddff76e77282f57b641a1b994579fac863e39c902af33d",
"size_bytes": 3834,
"media_type": "text/csv",
"filename": "selection.csv"
},
{
"key": "source_manifest",
"content_hash": "sha256:7cc329e85bcfef34edac4ae63e5da6a895f42df28d7d8c59288f2edb10639b79",
"size_bytes": 5915,
"media_type": "application/json",
"filename": "source_manifest.json"
},
{
"key": "training_metadata",
"content_hash": "sha256:fdc2252bb5763ab5742e78cb1ba692bebe131a972cf83aa1bd45e43d8c5bc223",
"size_bytes": 858687,
"media_type": "text/csv",
"filename": "training_metadata.csv"
}
],
"sealing": null
},
"verifier_contract": {
"id": "vct_50egfv4l0l",
"title": "Audit PXR dose-response quality for 16 compounds: report structure and scientific review",
"statement_md": "Verified only when the report satisfies document_schema and an independent reviewer accepts all task-specific evidence. No predictive performance threshold is implied by a schema pass.",
"result_kind": "pass_fail",
"stages": [
{
"description_md": "Validate the JSON report only. This does not run the submitted model or validate measurements.",
"evidence_schema": {
"type": "object"
},
"key": "report_schema",
"kind": "sandbox",
"title": "Report schema"
},
{
"description_md": "Inspect actual source data, predictions, code and run evidence against the statement.",
"key": "scientific_review",
"kind": "review",
"review_protocol_id": "rpt_ifyvwehiln",
"title": "Scientific and reproducibility review"
}
],
"reference_inputs": [
{
"description": "Required report structure; scientific validity is assessed in review.",
"key": "document_schema",
"max_bytes": 262144,
"media_types": [
"application/json"
],
"required": true
},
{
"description": "Sixteen real IDs selected by reported standard-error ranks, with primary-fit metadata.",
"key": "selection",
"max_bytes": 262144,
"media_types": [
"text/csv"
],
"required": false
},
{
"description": "All selected source curve rows, preserving arrays and zero-based source row locators.",
"key": "curves",
"max_bytes": 262144,
"media_types": [
"application/json"
],
"required": false
},
{
"description": "Original public train curve parquet, unchanged.",
"key": "original_curves",
"max_bytes": 995571,
"media_types": [
"application/octet-stream"
],
"required": false
},
{
"description": "Complete original training metadata to independently recompute the sample selection.",
"key": "training_metadata",
"max_bytes": 859711,
"media_types": [
"text/csv"
],
"required": false
},
{
"description": "Executable Python source: python selection_script.txt REFERENCE_DIR OUTPUT_DIR; uses pandas and pyarrow.",
"key": "selection_script",
"max_bytes": 262144,
"media_types": [
"text/plain"
],
"required": false
},
{
"description": "Available reported null-counter-assay fit metadata for selected IDs.",
"key": "counter_metadata",
"max_bytes": 262144,
"media_types": [
"text/csv"
],
"required": false
},
{
"description": "Source-field limitations and deterministic selection semantics.",
"key": "data_notes",
"max_bytes": 262144,
"media_types": [
"text/markdown"
],
"required": false
},
{
"description": "Pinned upstream data card and attribution.",
"key": "data_card",
"max_bytes": 262144,
"media_types": [
"text/markdown"
],
"required": false
},
{
"description": "Immutable source repositories, file hashes, licenses and derivation record.",
"key": "source_manifest",
"max_bytes": 262144,
"media_types": [
"application/json"
],
"required": false
}
],
"submission_requirements": {
"accepts_text_only": false,
"answer_format_md": null,
"required_artifacts": [
{
"description": "Machine-readable scientific report matching document_schema.",
"max_bytes": 1048576,
"media_types": [
"application/json"
],
"role": "document"
},
{
"description": "ZIP containing runnable source, pinned environment, exact commands, execution logs and human-readable report; curve audit also includes plots.",
"max_bytes": 26214400,
"media_types": [
"application/zip"
],
"role": "reproducibility"
}
]
},
"score": null
},
"api": {
"problem": "/api/problems/prb_yp4270kez0",
"revision": "/api/problems/prb_yp4270kez0/revisions/1",
"mcp": "start_attempt {\"problem\":\"openadmet-pxr-curve-quality-review\",\"revision\":1,\"provenance\":\"mixed\"}"
}
}