Identification of hypoxia-related diagnostic biomarkers and immune signatures in diminished ovarian reserve.

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[], "gaps": ["method", "targets"]}, "capability": {"state": "absent", "requirements": [], "gaps": ["capability"]}, "readiness": {"state": "partial", "tier": null, "blocking_axis": null, "blocked_on": null, "axes": {}, "can_run": {"dsl_operations": [], "assets": ["source:pmid:40832468"], "steps": ["read_published_estimate"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": ["xml"], "capabilities": [], "data_gaps": ["source:pmid:40832468"]}, "gaps": ["corpus_record_absent"]}, "review": {"state": "partial", "machine_critique": {"status": "blocked", "providers": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "prompt_version": "full-text-reading-v1", "prompt_hash": "6a1328da0e8bd0746d7e19c624b01bb499397ee8fc076537be0f0bbf754aac5c", "source_hash": "7694c85f81eb98315e39554b4eebfbe708b72d94cca140f37fe7ebb0719844f5", "raw_response_sha256": "sha256:880083794b92489060cbf204ab2b8df68a66e532f8853e43971b319d5f913c0a", "raw_response_chars": 5800}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "full-text-reading-v1", "prompt_hash": "2a07a98bf38484bc3813a2e36c68ea8d9eba7a26c235d87337f1a179cde4f115", "source_hash": "7694c85f81eb98315e39554b4eebfbe708b72d94cca140f37fe7ebb0719844f5", "raw_response_sha256": "sha256:878f864e7a219409fa3bc0d143f13eaf1db014f817b725d150b3339b051af5db", "raw_response_chars": 78287}], "target_providers": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "prompt_version": "replication-target-v2", "prompt_hash": "7de0918e7dbc2decc815dfa3da4f8a32a851bbab2d30b4068620ec1563464dee", "source_hash": "7694c85f81eb98315e39554b4eebfbe708b72d94cca140f37fe7ebb0719844f5", "raw_response": "{\"parent_value\":6,\"unit\":\"hub genes\",\"evidence\":\"In summary, we identified six hub genes associated with hypoxia and DOR, namely, FANCI, KAT2A, TACC3, TPX2, VHL, and WSB1.\",\"target_result\":\"Six hub genes associated with hypoxia and DOR: FANCI, KAT2A, TACC3, TPX2, VHL, and WSB1.\",\"number_stated\":true}", "reading": {"parent_value": 6, "unit": "hub genes", "evidence": "In summary, we identified six hub genes associated with hypoxia and DOR, namely, FANCI, KAT2A, TACC3, TPX2, VHL, and WSB1.", "target_result": "Six hub genes associated with hypoxia and DOR: FANCI, KAT2A, TACC3, TPX2, VHL, and WSB1.", "number_stated": true, "source_locator": "chars 7756-7878 of source sha256 7694c85f81eb98315e39554b4eebfbe708b72d94cca140f37fe7ebb0719844f5"}, "recorded_at": "2026-10-31T15:31:34.131471+00:00"}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "replication-target-v2", "prompt_hash": "3b5d5034ce4144f04858e861d99a98c05d55d3a487f17ee606d0ff4e47881c72", "source_hash": "7694c85f81eb98315e39554b4eebfbe708b72d94cca140f37fe7ebb0719844f5", "raw_response": "<think>We need answer JSON only. Need interpret target \"headline numerical result paper states for its main finding\". Source gives multiple numbers: 12 hypoxia-related genes diff expressed, 17 linked, eight pathways, six hub genes, five pathways. Which single numerical result replication registered target has reproduce, headline numerical result for main finding. Likely six hub genes identified. Need report headline number only: value paper states for registered target, unit paper prints, exact contiguous quote contains number; when linked by wording, quote whole clause. The conclusion: \"In summary, we identified six hub genes associated with hypoxia and DOR, namely...\" This is headline numerical result main finding. Unit could \"hub genes\" perhaps unit printed? They ask headline number only, value and unit paper prints. Number is 6, unit perhaps \"hub genes\". Evidence exact clause. Maybe evidence needs exact contiguous quotation containing number, likely whole sentence: \"In summary, we identified six hub genes associated with hypoxia and DOR, namely, FANCI, KAT2A, TACC3, TPX2, VHL, and WSB1.\" It links six hub genes directly. parent_value 6; unit \"hub genes\". target_result maybe \"Six hub genes...\" They specifically \"Report the headline number only\" but schema target_result string. We need perhaps target_result describes. \"The paper identifies six hub genes associated with hypoxia and DOR...\" Yet headline number only likely parent value, target result perhaps statement. Need adhere.\n\nQuestion wording: \"Read supplied paper text and find the single numerical result that a replication of the registered target has to reproduce. Report the headline number only: the value the paper itself states for the registered target, not a value you calculated, converted, averaged or reconstructed. The unit must be the unit the paper prints.\" So likely parent_value 6, unit \"hub genes\", evidence quote. target_result likely \"Six hub genes associated with hypoxia and DOR were identified.\" number_stated true.\n\nCould headline be twelve hypoxia-related genes? Abstract results first sentence \"Twelve hypoxia-related genes were differentially expressed between low ovarian reserve (LOR) and high ovarian reserve (HOR), with 17 linked to DOR; eight pathways differed...\" But conclusion main finding emphasizes six hub genes. Registered target generic \"headline numerical result the paper states for its main finding\". Need infer intended singular target from title/abstract. Main finding = identification of biomarkers/immune signatures, headline count likely six hub genes. Conclusion explicitly \"we identified six hub genes\". Strong.\n\nExact evidence should maybe include whole sentence to validate attribution. Unit \"hub genes\" is not a formal unit but printed noun. Should unit perhaps \"genes\" only? \"unit must be unit the paper prints.\" Paper says \"six hub genes\". Use \"hub genes\". JSON valid, no markdown.\n\nCould parent_value number only as 6. target_result perhaps \"Six hub genes associated with hypoxia and DOR were identified.\" They request headline number only maybe don't list gene names? Evidence includes names because exact contiguous clause whole sentence needed to check attribution. Could quote only clause: \"we identified six hub genes associated with hypoxia and DOR\" This is exact contiguous quotation and contains attribution, without gene list. They say \"When that is how text links them, quote the whole clause so reader can check attribution.\" Full clause is sufficient. Need evidence exact quote from source. \"In summary, we identified six hub genes associated with hypoxia and DOR, namely, FANCI, KAT2A, TACC3, TPX2, VHL, and WSB1.\" is exact full sentence. It contains number. Good.\n\nMaybe target_result must only number? Schema says string. In these tasks likely expected a textual description. User says \"Report headline number only\" likely means not secondary numbers. Could target_result = \"Six hub genes associated with hypoxia and DOR were identified.\" This includes only headline number.\n\nLet's ensure no numerical mismatch: abstract says six hub genes. Conclusion same. No unit like \"genes\" explicitly numerical count. Yes.\n\nNeed output exact JSON object.</think>\n\n{\"parent_value\":6,\"unit\":\"hub genes\",\"evidence\":\"In summary, we identified six hub genes associated with hypoxia and DOR, namely, FANCI, KAT2A, TACC3, TPX2, VHL, and WSB1.\",\"target_result\":\"Six hub genes associated with hypoxia and DOR were identified.\",\"number_stated\":true}", "reading": {"parent_value": 6, "unit": "hub genes", "evidence": "In summary, we identified six hub genes associated with hypoxia and DOR, namely, FANCI, KAT2A, TACC3, TPX2, VHL, and WSB1.", "target_result": "Six hub genes associated with hypoxia and DOR were identified.", "number_stated": true, "source_locator": "chars 7756-7878 of source sha256 7694c85f81eb98315e39554b4eebfbe708b72d94cca140f37fe7ebb0719844f5"}, "recorded_at": "2026-10-31T15:31:35.138986+00:00"}], "agreement": false, "disagreements": {"target_result": {"minimax": "Twelve hypoxia-related genes were differentially expressed between low ovarian reserve and high ovarian reserve groups, 17 genes were linked to diminished ovarian reserve, eight pathways differed between the groups, and six hub genes—FANCI, KAT2A, TACC3, TPX2, VHL, and WSB1—were identified.", "minimax_alt": "In summary, we identified six hub genes associated with hypoxia and DOR, namely, FANCI, KAT2A, TACC3, TPX2, VHL, and WSB1. These genes were validated in the context of immune infiltration.", "decisive": false}, "physical_methods": {"minimax": ["Granulosa cell injury model using 4-hydroperoxycyclophosphamide (4-HC)", "Quantitative real-time PCR", "Western blot", "Cell Counting Kit-8 assay", "Flow cytometry"], "minimax_alt": ["Granulosa cell injury model created using 4-hydroperoxycyclophosphamide (4-HC)", "Quantitative real-time PCR for FANCI and KAT2A expression", "Western blot for FANCI and KAT2A expression", "Cell Counting Kit-8 assay for assessing cell proliferation and viability", "Flow cytometry for assessing apoptosis"], "decisive": false}, "analysis_methods": {"minimax": ["Common differentially expressed gene normalization", "GeneCards-based identification of hypoxia-related differentially expressed genes", "Receiver Operating Characteristic (ROC) curve analysis", "STRING protein-protein interaction network analysis", "Cytoscape network visualization", "Gene Ontology (GO) enrichment analysis", "Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis", "Gene set enrichment analysis (GSEA)", "Gene set variation analysis (GSVA)", "CIBERSORT immune cell infiltration analysis using the LM22 feature gene matrix", "Spearman correlation analysis"], "minimax_alt": ["Common differentially expressed gene (Co-DEG) normalization", "GeneCards-based identification of hypoxia-related differentially expressed genes (HRDEGs)", "Receiver Operating Characteristic (ROC) curve analysis", "STRING and Cytoscape protein-protein interaction network analysis", "Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis", "Gene set enrichment analysis (GSEA) using clusterProfiler", "Gene set variation analysis (GSVA)", "CIBERSORT immune cell infiltration analysis using the LM22 feature gene matrix", "Spearman correlation analysis and hotspot-map visualization using ggplot2", "Wilcoxon rank-sum test for comparisons between groups"], "decisive": false}, "statistical_method": {"minimax": "Wilcoxon rank-sum test", "minimax_alt": "Wilcoxon rank-sum test for between-group comparisons and Spearman test for correlations, using p < 0.05 as the significance threshold", "decisive": true}}, "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": "blocked", "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.blocked"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "package:f9e2a1f6de7e949e2a9d4b9fd323be4fdaddfa0834aed828a1cafd31b939f9bd", "type": "sep_package", "label": "SEP v1 package for pmid:40832468"}], "activities": [{"id": "activity:conversion:pmid:40832468", "type": "conversion", "used": ["package:f9e2a1f6de7e949e2a9d4b9fd323be4fdaddfa0834aed828a1cafd31b939f9bd"], "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": "08ddaed5-5f31-4d65-aa98-cb8adfcc4115", "parent_hash": "f9e2a1f6de7e949e2a9d4b9fd323be4fdaddfa0834aed828a1cafd31b939f9bd", "fork_of": null, "generation": 1}, "gaps": ["abstract", "asset:source:pmid:40832468 not verified", "authors", "capability", "corpus_record_absent", "execution.not_run", "method", "review.human_critique", "review.machine_critique.blocked", "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:40832468' does not resolve to a declared asset", "targets"]}