{"data":{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40832057", "kind": "science-record", "revision": 4, "content_hash": "sha256:093f9c531259febf977468dc8ee8875aa20279c90b2e46b81e71625e1602a5f2", "created_at": "2026-11-01T20:30:56Z", "updated_at": "2026-11-01T22:57:03Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of Ifitm1 as a Pivotal Gene in Mouse Spinal Cord Injury Using Comprehensive Machine Learning Algorithms.", "doi": "10.1155/mi/6149780", "pmid": "40832057", "authors": ["Yu Yao", "Kun Xi", "Shaohu Xu", "Feiyu Zhang", "Liang Chen"], "journal": "Mediators of inflammation", "year": 2025, "abstract": "Background: Spinal cord injury (SCI) functions as a medical condition leading to substantial motor and neurological system deteriorations. Researchers must understand the molecular mechanisms of this disease because it serves as a foundation for creating therapeutic solutions. Methods: This study analyzed the single-cell dataset GSE189070 and microarray datasets GSE47681, GSE92657, and GSE93561 retrieved from the GEO database. Using R packages \"Seurat\" and \"Celldex,\" we identified and annotated cell clusters in single-cell data. Combined microarray datasets underwent differential expression analysis, WGCNA, and machine learning to identify key hub genes. Immune cell associations were assessed using Cibersort, while the connection map (CMap) database was employed to predict small-molecule drugs targeting the identified genes. Experimental validation confirmed findings. Results: In datasets involving single cells, granulocyte subpopulations denote unique cellular populations related to SCI. The high-dimensional weighted gene co-expression network analysis (hdWGCNA) algorithm pinpointed crucial modules linked to granulocyte subgroups, particularly from the black, green, and yellow modules. In the SCI cohort, Ifitm1 emerged as a potential hub gene. Importantly, Ifitm1 shows a significant positive correlation with M1 macrophages. Utilizing the CMap database along with molecular docking investigations, the small-molecule drug NVP-AUY922, which interacts with Ifitm1, was discovered. Experimental assessments revealed that Ifitm1 is linked to macrophage inflammation following SCI. Conclusion: This study revealed the importance of granulocyte subsets and Ifitm1 in SCI, proposed Ifitm1 as a potential therapeutic target, and provided new insights into the molecular mechanisms of SCI.", "claims": [{"id": "claim-method", "statement": "In our analysis of SCI samples compared to normal samples, we employed the “limma” R package to perform a differential expression assessment, with the objective of identifying DEGs.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40832057", "locator": "sections[7] \"2.5. Identification of DEGs\" paragraph 2", "quote": "In our analysis of SCI samples compared to normal samples, we employed the “limma” R package to perform a differential expression assessment, with the objective of identifying DEGs."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets analyzed in the current study (GSE47681, GSE92657, GSE93561, and GSE189070) are available in the GEO repository (https://www.ncbi.nlm.nih.gov/geo/).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40832057", "locator": "sections[34] \"Data Availability Statement\" paragraph 2", "quote": "The datasets analyzed in the current study (GSE47681, GSE92657, GSE93561, and GSE189070) are available in the GEO repository (https://www.ncbi.nlm.nih.gov/geo/)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Ifitm1 was identified as the principal SCI-associated gene and achieved an ROC AUC of 0.939.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40832057", "locator": "sections[26] \"3.5. Identification and Evaluation of Important Biomarkers\" paragraph 2", "quote": "As a result, we identified Ifitm1 as the principal gene that has the most substantial influence on model predictions."}, {"asset": "source:pmid:40832057", "locator": "sections[26] \"3.5. Identification and Evaluation of Important Biomarkers\" paragraph 2", "quote": "The findings indicated that the area under the curve (AUC) for Ifitm1 is 0.939 (Figure 5D)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Ifitm1 was identified as the principal SCI-associated gene and achieved an ROC AUC of 0.939.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:40832057"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE189070"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE189070"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:40832057", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/mi/6149780", "sha256": 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Records without an assay match currently receive a zero-hour model value.","status":"unverified","severity":"high"},{"code":"signal_score_without_citations","basis":["5,529 of 5,529 records (100.0%) have no citation count from the source metadata."],"claim":"Signal score","gloss":"The signal score uses publication-type weight because the mirror supplied zero citation counts.","detail":"The source supplied no citation counts for any record in this run, so the signal score is publication-type weight only. The citation term of the ranking is inert here, and the shortlist is ordered by publication type alone.","status":"unverified","severity":"high"},{"code":"abstract_absent","basis":["1,667 of 5,529 records (30.2%) carry no abstract at all."],"claim":"Evidence base for classification","gloss":"Some records contain a title and publication type only, defining the available classification evidence.","detail":"Where the mirror contains a title and publication types only, those fields define the classifier evidence. A methods section is required for fuller automated and human review.","status":"unverified","severity":"medium"},{"code":"classifier_agreement_measured","basis":["Published two-way decision agreement 77.7% (310 of 399 decidable records) from a stratified hand-check of 438 real records.","Three-way diagnostic agreement 73.9% (288 of 390 decidable records).","data_only agreement 75.2% (100 of 133 decidable).","48 record(s) could not be decided from title and abstract and were excluded from the denominator.","56 analysis-only records were published under another work type, so the data_only share is not an upper bound."],"claim":"Published automatable decision","gloss":"This figure has been checked against a human reading the same papers, so we know how often it is right.","detail":"The published automatable / not-automatable distribution comes from a rule-based classifier that was hand-checked against a fixed ground-truth definition. The agreement rates below are measured, not estimated. The three-way work type remains a diagnostic and is reported separately.","status":"measured","severity":"high"},{"code":"llm_comparison_not_measured","basis":["rule_based_v1+lex99e1195c7d6f produced 5,529 of 5,529 classifications.","Measured on 438 labelled records; these are RULE-BASED figures, not model results."],"claim":"Rule-based versus LLM agreement","gloss":"Every number here is the rule engine’s own. Model comparison begins when a working API credential is connected and measured.","detail":"The published two-way decision agreed with a human reading on 310 of 399 decidable records (77.7%). The diagnostic three-way label agreed on 288 of 390 decidable records (73.9%). Every percentage in this run belongs to the rule engine. Model comparison begins when a working API credential is connected and measured.","status":"not_measured","severity":"high"},{"code":"confidence_is_a_band","basis":["low band: 135 of 210 hand-judged records were correct, 64.3% [57.6, 70.5] (95% CI).","medium band: 80 of 104 hand-judged records were correct, 76.9% [68.0, 84.0] (95% CI).","high band: 73 of 76 hand-judged records were correct, 96.0% [89.0, 98.7] (95% CI).","A fitted calibrated probability was built, measured and withdrawn: it overstated held-out accuracy and reorders nothing."],"claim":"Confidence band and evidence score","gloss":"The confidence band carries a measured accuracy interval; 0.85 represents relative rank strength.","detail":"Confidence on this run is a BAND plus its measured accuracy interval. The number stored alongside each record is a monotone evidence score that orders records; 0.85 represents relative rank strength. A fitted probability was withdrawn after it overstated held-out accuracy. Threshold on the band.","status":"measured","severity":"medium"},{"code":"three_way_split_is_diagnostic","basis":["The corpus is published at the two-way decision: automatable or not-automatable. The three-way split (data_only / physical / mixed) is published as a diagnostic with its measured reliability attached, not as a claim, because the rule engine's `mixed` call cannot be defended.","The engine called 22 record(s) mixed; 10 matched the human judgement (45.5%, 95% CI 26.9-65.3).","The engine's `mixed` call is right on 10/22 hand-judged records (45.5%, 95% CI 26.9%-65.3%); a constant `physical` guess scores 36.4%.","The engine's `mixed` call does not reliably beat a constant `physical` guess on the hand-judged records it labels mixed.","The sign of that difference flips between two independent samples, so the three-way refinement is not demonstrably informative.","The mixed stratum contributes a disproportionate share of errors relative to its size.","At title-only depth the physical/mixed split collapses: a title says that work was done, not whether it was also analysed."],"claim":"The published decision is two-way","gloss":"The three-way split is shown for diagnosis only. The published split is two ways.","detail":"Count and filter the corpus on automatable versus not-automatable. The data_only / physical / mixed split remains an internal engine diagnostic because the mixed call has lower measured reliability.","status":"measured","severity":"medium"},{"code":"automatable_flag_unproven","basis":["6 of 29 assay families are marked automatable now: meta_analysis, machine_learning, survival_analysis, pca, molecular_docking, differential_expression.","The flag is a rule over assay family and work type; validation begins with the first executed replication.","It inherits the 75.2% data_only agreement rate, because the flag requires the record to be analysis-only."],"claim":"Automatable now","gloss":"This flag marks assay families the rules classify as data-only. The first executed replication will validate it.","detail":"This flag marks families the rules consider replicable from data alone. Its validity depends on the analysis-only classification and will be measured through an executed replication.","status":"unverified","severity":"medium"}],"confidence_policy":"band_with_measured_interval","confidence_contract":{"policy":"band_with_measured_interval","summary":"Confidence is reported as a BAND with a measured accuracy interval. The raw evidence score supplies monotone ordering. A fitted point estimate was withdrawn after it overstated held-out accuracy.","evidence_score":"A monotone evidence score in [0,1] built from cue mass, axis separation and text coverage. Use it to order records. Interpret 0.85 as relative rank strength.","confidence_band":"low | medium | high. Consumers threshold on this value.","band_accuracy":"Wilson 95% interval on the measured agreement of the hand-judged records in this band.","calibrated_confidence":"WITHDRAWN. Reintroduction requires held-out evidence demonstrating reliable estimates across every bin."},"band_accuracy":{"low":{"n":210,"low":0.576,"band":"low","high":0.7046,"agree":135,"accuracy":0.6429},"high":{"n":76,"low":0.8903,"band":"high","high":0.9865,"agree":73,"accuracy":0.9605},"medium":{"n":104,"low":0.6795,"band":"medium","high":0.8397,"agree":80,"accuracy":0.7692}},"provider":"rule_based_v1+lex99e1195c7d6f","lexicon_id":"99e1195c7d6f","contract_published_at":"2026-10-23T12:25:29.022232+00:00","confidence_is_band":true,"confidence_is_probability":false,"decision_taxonomy":"two_way","decidable_fraction_two_way":0.8854,"decidable_fraction_two_way_low":0.8565,"decidable_fraction_two_way_high":0.9143,"decidable_fraction_three_way":0.8586,"decidable_fraction_three_way_low":0.8287,"decidable_fraction_three_way_high":0.8884,"decidable_population":5529,"validation_sample_size":438,"three_way_cost_fraction":0.0268,"three_way_cost_records":148,"decision_counts":{"automatable":230,"not_automatable":5299},"decision_split":{"automatable":{"count":230,"share":0.04159884246699222},"not_automatable":{"count":5299,"share":0.9584011575330078}},"diagnostic_work_type_counts":{"mixed":24,"physical":5275,"data_only":230}}}