Single-cell characterization of the immune heterogeneity of pulmonary hypertension identifies novel targets for immunotherapy.

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"51f27395813fb52551edd7ff7a7bc6cfd72d8ab5ab3cb405d0951c74f96d6156", "source_hash": "5bc7296bc5fe4573a597e65ca5f0624f56c8f39e18c99d00c303bf01d7d42b00", "raw_response_sha256": "sha256:0bcadcef6ffe804be209ca11ce5fb1f1d6d763dcb59dbdbb426f7e9098e9823c", "raw_response_chars": 74650}], "target_providers": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "prompt_version": "replication-target-v2", "prompt_hash": "9d3c60eff198814402f0c1060be070400eed0c712d8711f003bdbcea8a033536", "source_hash": "5bc7296bc5fe4573a597e65ca5f0624f56c8f39e18c99d00c303bf01d7d42b00", "raw_response": "{\"parent_value\":124561,\"unit\":\"cells\",\"evidence\":\"In total, approximately 124,561 cells were analyzed and a total 34 clusters were identified.\",\"target_result\":\"Approximately 124,561 cells were analyzed.\",\"number_stated\":true}", "reading": {"parent_value": 124561, "unit": "cells", "evidence": "In total, approximately 124,561 cells were analyzed and a total 34 clusters were identified.", "target_result": "Approximately 124,561 cells were analyzed.", "number_stated": true, "source_locator": "chars 898-990 of source sha256 5bc7296bc5fe4573a597e65ca5f0624f56c8f39e18c99d00c303bf01d7d42b00"}, "recorded_at": "2026-10-31T15:23:55.280002+00:00"}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "replication-target-v2", "prompt_hash": "9a11f100ea90b33880b63d66841066d9fef54c9c413297091315634abb39acd8", "source_hash": "5bc7296bc5fe4573a597e65ca5f0624f56c8f39e18c99d00c303bf01d7d42b00", "raw_response": "<think>We need answer JSON only. Need identify single numerical result replication registered target headline numerical result paper states main finding. Source abstract gives approximately 124,561 cells analyzed and 34 clusters. Which headline number? User says single numerical result paper itself states for registered target. Registered target generic: headline numerical result paper states for main finding. Need likely 124,561 cells is headline result. Need exact contiguous quote containing number, whole clause perhaps \"In total, approximately 124,561 cells were analyzed and a total 34 clusters were identified.\" But asks headline number only value, unit paper prints. Unit \"cells\". Evidence exact contiguous quote. target_result likely \"Approximately 124,561 cells were analyzed.\" Need parent_value number 124561, unit perhaps \"cells\" or maybe no printed unit after number, wording cells. Evidence can include sentence with both numbers but value only one? They want single numerical result. Maybe quote clause around number. Exact: \"In total, approximately 124,561 cells were analyzed and a total 34 clusters were identified.\" This contains another number 34. They ask headline number only. Could quote whole clause inevitably second number. Is there a narrower exact contiguous quote: \"approximately 124,561 cells were analyzed\" is exact contiguous and contains number, attribution? It states exactly. But instruction says attribution may be carried wording; quote whole clause so reader can check. Full sentence is safe. Yet \"headline number only\" likely output number only in parent_value, but evidence can contain other source numbers if full quote. Maybe choose quote \"In total, approximately 124,561 cells were analyzed\" exact contiguous; it is a clause and target is clearly result. They specifically say exact contiguous quotation containing number; do not shorten it. \"do not shorten it\" might mean quote full clause/sentence, not selectively truncate. Use full sentence.\n\nBut need consider perhaps main headline numerical result is 34 clusters, or 124,561 cells? \"headline numerical result\" replication target likely abstract's key count. Usually benchmark asks extract \"single numerical result\" from paper. The main quantitative result likely number of cells and clusters; but registered target singular headline numerical result. In abstract: \"In total, approximately 124,561 cells were analyzed and a total 34 clusters were identified.\" Which one is headline? They might expect 124,561 cells because more headline, perhaps \"approximately 124,561 cells were analyzed\" and unit cells. The 34 clusters equally a numerical result. The prompt says \"single numerical result\" likely source contains a target phrase somewhere in paper. But target is generic, perhaps evaluation expects identify headline number from text. Need infer intended.\n\nLet's parse request framing. \"Read the 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.\" Registered target: \"the headline numerical result the paper states for its main finding\". This likely generated benchmark where target description could be vague. They expect headline number stated in source. In paper abstract, headline number likely 124,561 cells analyzed and 34 clusters identified. But \"single numerical result\" perhaps one number attached to main finding. There are multiple. Maybe title and abstract first quantitative: 124,561 cells and 34 clusters. Which is headline? Maybe the result is \"approximately 124,561 cells were analyzed and a total 34 clusters were identified\"—two numbers, conflicting with \"single\". They specifically say \"headline number only\", perhaps target number is 124,561 and 34 clusters is a secondary method metric. Need choose 124,561 cells.\n\nCould \"headline numerical result\" be 34 clusters? Abstract:\n\"We performed single-cell RNA sequencing ... In total, approximately 124,561 cells were analyzed and a total 34 clusters were identified.\"\nA replication's central output might reproduce 34 cell clusters. The cells analyzed is dataset scale, while number of identified clusters is result. But \"headline number\" could be 124,561, often abstract headline first. Registered target explicitly says \"for its main finding\", paper main finding is immune heterogeneity and novel targets GPNMB, with no singular quantitative finding. The only abstract counts are 124,561 cells and 34 clusters. Which is \"headline numerical result\"? Maybe they consider whole sentence's \"approximately 124,561 cells\" as headline. User asks \"the value the paper itself states for the registered target\", no calculated. We need formulate target_result perhaps \"The paper states that approximately 124,561 cells were analyzed.\" number_stated true. Evidence exact quote. Unit \"cells\". Could unit be \"cells analyzed\" to preserve printed semantic unit? Unit the paper prints: \"cells\". Use cells.\n\nJSON valid. Ensure no commas in number issue JSON supports 124561. Evidence exact.</think>\n\n{\"parent_value\":124561,\"unit\":\"cells\",\"evidence\":\"In total, approximately 124,561 cells were analyzed and a total 34 clusters were identified.\",\"target_result\":\"The paper states that approximately 124,561 cells were analyzed.\",\"number_stated\":true}", "reading": {"parent_value": 124561, "unit": "cells", "evidence": "In total, approximately 124,561 cells were analyzed and a total 34 clusters were identified.", "target_result": "The paper states that approximately 124,561 cells were analyzed.", "number_stated": true, "source_locator": "chars 898-990 of source sha256 5bc7296bc5fe4573a597e65ca5f0624f56c8f39e18c99d00c303bf01d7d42b00"}, "recorded_at": "2026-10-31T15:23:59.684730+00:00"}], "agreement": true, "disagreements": {"target_result": {"minimax": "Approximately 124,561 cells were analyzed and a total of 34 clusters were identified.", "minimax_alt": "In total, approximately 124,561 cells were analyzed and a total 34 clusters were identified.", "decisive": false}, "analysis_methods": {"minimax": ["Single-cell RNA sequencing", "Integrated scRNA-seq analysis", "Clustering analysis", "Monocle2 trajectory analysis", "KEGG and GO enrichment analysis", "SCENIC regulatory-network analysis", "CellChat cell-cell communication analysis", "scMLnet and multiichenet signaling-network analysis", "Spearman correlation analysis"], "minimax_alt": ["single-cell RNA sequencing (scRNA-seq)", "integrated scRNA-seq bioinformatics analysis", "clustering 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:9fc7c22b7141b54d58791a4d6b1160aa7d401165ae6c8e4b6f2b580e81bd2c89", "type": "sep_package", "label": "SEP v1 package for pmid:39930365"}], "activities": [{"id": "activity:conversion:pmid:39930365", "type": "conversion", "used": ["package:9fc7c22b7141b54d58791a4d6b1160aa7d401165ae6c8e4b6f2b580e81bd2c89"], "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": "pmid:39930365", "parent_hash": "sha256:dc412abcebe780ebb2e8a2c7375a7698f9d41363fb8166a0c317a523b8f34ae5", "fork_of": null, "generation": 2}, "gaps": ["abstract", "asset:source:pmid:39930365 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:39930365' does not resolve to a declared asset", "targets"]}