A phase separation-related gene signature for prognosis prediction and immunotherapy response evaluation in gastric cancer with targeted natural compound discovery.

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"bfacd7080c43c92ebb80f6e7f72237920d7a7e4fe88674b465fbb2621a6cd380", "raw_response_sha256": "sha256:c97b4756f82a7f68d72970d773b93e713f90fa6451034009f5f11a2ff1722ef5", "raw_response_chars": 6454}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "full-text-reading-v1", "prompt_hash": "1fe65bc0b82dd6d74b8ac557a3dfb28cc55484d9861af854e01a17eaa898ae50", "source_hash": "bfacd7080c43c92ebb80f6e7f72237920d7a7e4fe88674b465fbb2621a6cd380", "raw_response_sha256": "sha256:2de93e9661f768e8e4e2af0a4b6e5439b24b9d460ffb8134604cda02633218c3", "raw_response_chars": 67342}], "target_providers": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "prompt_version": "replication-target-v2", "prompt_hash": "fa71f379eed7fe620d5ee71111fb833df25bf56666e218d4bfa6bc6a89ae5bae", "source_hash": "bfacd7080c43c92ebb80f6e7f72237920d7a7e4fe88674b465fbb2621a6cd380", "raw_response": "{\"parent_value\":21,\"unit\":\"genes\",\"evidence\":\"By Integrating analysis of the differential expression dataset from TCGA-STAD (n = 407, 375 tumor/32 normal) with prognosis-related dataset and PS-related dataset, we identified 78 candidate genes and developed a robust 21-gene risk prediction model.\",\"target_result\":\"The paper states that it developed a robust 21-gene risk prediction model.\",\"number_stated\":true}", "reading": {"parent_value": 21, "unit": "genes", "evidence": "By Integrating analysis of the differential expression dataset from TCGA-STAD (n = 407, 375 tumor/32 normal) with prognosis-related dataset and PS-related dataset, we identified 78 candidate genes and developed a robust 21-gene risk prediction model.", "target_result": "The paper states that it developed a robust 21-gene risk prediction model.", "number_stated": true, "source_locator": "chars 1251-1501 of source sha256 bfacd7080c43c92ebb80f6e7f72237920d7a7e4fe88674b465fbb2621a6cd380"}, "recorded_at": "2026-10-31T15:27:05.148074+00:00"}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "replication-target-v2", "prompt_hash": "5c157734cbfafe8440d98cdc45767951de7e6aa3767970a3982ba159d5bcfb7a", "source_hash": "bfacd7080c43c92ebb80f6e7f72237920d7a7e4fe88674b465fbb2621a6cd380", "raw_response": "<think>We need answer JSON only. Need identify single numerical result replication registered target headline numerical result paper states for main finding. Source abstract/results says identified 78 candidate genes and developed robust 21-gene risk prediction model. Which headline number? \"robust 21-gene risk prediction model\" likely target numerical result main finding. Need report value paper states for registered target, unit as paper prints. Evidence exact contiguous quote containing number, attribution via wording. Could quote whole clause: \"By Integrating analysis of the differential expression dataset from TCGA-STAD (n = 407, 375 tumor/32 normal) with prognosis-related dataset and PS-related dataset, we identified 78 candidate genes and developed a robust 21-gene risk prediction model.\" But headline numerical result likely 21-gene risk prediction model. Unit perhaps \"genes\" or \"gene\"? Paper prints \"21-gene\". Request unit must be unit paper prints. Likely unit \"genes\" maybe number 21, unit \"genes\". Evidence exact quote should attach target. Could quote \"we identified 78 candidate genes and developed a robust 21-gene risk prediction model.\" This is exact contiguous quotation and contains both 78 and 21, but asks single headline number and evidence contains number. They may prefer quote whole clause. If quote has 78, ambiguity? Exact contiguous quotation can have other nums. \"developed a robust 21-gene risk prediction model.\" is exact contiguous and direct. Evidence can be that phrase, no ellipsis. It is exact. Unit \"genes\" printed as compound unit. target_result perhaps \"21-gene risk prediction model\". number_stated true. Need make valid JSON.\n\nCould main finding instead number of candidate genes? Title main finding: phase separation-related gene signature, robust 21-gene risk prediction model. Headline number likely 21. \"The single numerical result that a replication ... has to reproduce\" likely 21-gene model. Need maybe docking scores &gt;6.0, 18 compounds, 13 high affinity, cohorts sizes. Clearly 21-gene risk model headline.\n\nUnit must unit paper prints. JSON \"unit\":\"genes\". Is \"21-gene\" unit printed singular adjectival. They might expect unit \"genes\". Usually extraction schema parent_value number, unit. If source says \"21-gene risk prediction model\", unit = \"genes\". Could be \"gene\" because exactly paper prints 21-gene. User says unit must be the unit paper prints. likely \"genes\" accepted. Need evidence exact contiguous quotation. Could use \"developed a robust 21-gene risk prediction model.\" Exact. target_result \"21-gene risk prediction model\". Let's ensure evidence quote includes direct target and number. Yes.\n\nMaybe they want full sentence because attribution may need whole clause. We can quote full relevant sentence, though it includes 78. But then headline result still 21. The instruction \"Report the headline number only\" applies output number, evidence can contain multiple? They explicitly evidence exact quote containing number. A narrower exact substring is ideal: \"developed a robust 21-gene risk prediction model.\" It directly links number. Quote punctuation exact. Is it contiguous? yes. Doesn't need whole clause? They say when attribution via words that name target directly, quote whole clause so reader can check. Whole clause likely \"we identified 78 candidate genes and developed a robust 21-gene risk prediction model.\" It contains extra 78, violating perhaps headline number only only evidence. Could quote predicate \"developed a robust 21-gene risk prediction model\" which is clause? The subject \"we\" omitted if quote starts developed, but phrase itself perhaps not grammatically standalone. Could quote \"we identified 78 candidate genes and developed a robust 21-gene risk prediction model.\" Exact contiguous. They may assess evidence matching expected answer and might prefer it. Yet \"single numerical result\" perhaps they expect a specific number among multiple, and evidence can include several. We could quote \"a robust 21-gene risk prediction model\" exact phrase, but no verb attribution. Still number attached directly to target by wording.\n\nNeed output no markdown.</think>\n\n{\"parent_value\":21,\"unit\":\"genes\",\"evidence\":\"developed a robust 21-gene risk prediction model.\",\"target_result\":\"21-gene risk prediction model\",\"number_stated\":true}", "reading": {"parent_value": 21, "unit": "genes", "evidence": "developed a robust 21-gene risk prediction model.", "target_result": "21-gene risk prediction model", "number_stated": true, "source_locator": "chars 1452-1501 of source sha256 bfacd7080c43c92ebb80f6e7f72237920d7a7e4fe88674b465fbb2621a6cd380"}, "recorded_at": "2026-10-31T15:27:11.224587+00:00"}], "agreement": true, "disagreements": {"target_result": {"minimax": "A robust 21-gene phase-separation-related risk prediction model that stratifies gastric cancer patients into high- and low-risk groups.", "minimax_alt": "A robust 21-gene risk prediction model was developed after 78 candidate genes were identified.", "decisive": false}, "analysis_methods": {"minimax": ["least absolute shrinkage and selection operator (LASSO) regression", "survival analysis", "gene set variation analysis (GSVA)", "single-sample gene-set enrichment analysis (ssGSEA)", "Tumor Immune Dysfunction and Exclusion (TIDE) server analysis", "Connectivity Map analysis", "HERB database analysis", "molecular docking validation"], "minimax_alt": ["least absolute shrinkage and selection operator (LASSO) regression", "survival analysis"], "decisive": false}}, "agreement_basis": {"policy": "decisive_fields", "decisive_fields": ["work_type", "number_stated", "parent_value", "unit"]}, "blinded": true}, "human_critique": {"status": "not_run", "reviewer": null, "signed_at": null, "conflict_checked": false, "commentary": null}, "stages": [{"key": "target_materials", "status": "pending", "reason": null, "evidence": null}, {"key": "independent_readings", "status": "passed", "reason": "The independent readings are incomplete or disagree; the source evidence must resolve the difference.", "evidence": {"provider_errors": []}}, {"key": "source_resolution", "status": "pending", "reason": null, "evidence": null}, {"key": "protocol_reconstruction", "status": "pending", "reason": null, "evidence": null}, {"key": "control_execution", "status": "pending", "reason": null, "evidence": null}, {"key": "control_comparison", "status": "pending", "reason": null, "evidence": null}, {"key": "publication", "status": "pending", "reason": null, "evidence": null}], "gaps": ["review.human_critique", "review.machine_critique.passed"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "package:601cc987df9975dda8e888e74dbd3007386d8af3e3e497b292ab1a4d5034fd7e", "type": "sep_package", "label": "SEP v1 package for pmid:40699463"}], "activities": [{"id": "activity:conversion:pmid:40699463", "type": "conversion", "used": ["package:601cc987df9975dda8e888e74dbd3007386d8af3e3e497b292ab1a4d5034fd7e"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:minimax", "type": "model", "label": "minimax"}, {"id": "agent:minimax_alt", "type": "model", "label": "minimax_alt"}, {"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}], "source_run_id": "run-20261023T122449232913", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "1fe93ccc-3e1f-47c0-ad39-6c3f10893be3", "parent_hash": "601cc987df9975dda8e888e74dbd3007386d8af3e3e497b292ab1a4d5034fd7e", "fork_of": null, "generation": 1}, "gaps": ["abstract", "asset:source:pmid:40699463 not verified", "authors", "capability", "corpus_record_absent", "execution.not_run", "method", "review.human_critique", "review.machine_critique.passed", "step:obtain_source_data blocked on data:not_downloaded", "step:run_analysis blocked on no owned computational capability is bound to this experiment", "step:run_analysis input 'materials:the source data behind the published result in pmid:40699463' does not resolve to a declared asset", "targets"]}