{"id":"W4415292260","doi":"10.1016/j.bjane.2025.844687","title":"Retrospective review of spinal magnetic resonance images to determine the margin of safety for epidural analgesia in pediatric patients","year":2025,"lang":"en","type":"article","venue":"Brazilian Journal of Anesthesiology (English Edition)","topic":"Anesthesia and Pain Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Queen's University","funders":"Queen's University","keywords":"Margin (machine learning); Magnetic resonance imaging; Retrospective cohort study; Central nervous system disease; Regional anesthesia; Complication","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001498777,0.0001702191,0.0007934874,0.0003846126,0.00004979964,0.000003928797,0.0002929574,0.00008753486,0.00007397834],"category_scores_gemma":[0.002095635,0.0001201497,0.0002462066,0.0006363991,0.0001679241,0.00009431397,0.00002561247,0.000229427,0.000001485536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008009918,"about_ca_system_score_gemma":0.0001621414,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002019765,"about_ca_topic_score_gemma":0.000002215647,"domain_scores_codex":[0.9979095,0.0002825794,0.001113685,0.0002024111,0.0002605927,0.0002312601],"domain_scores_gemma":[0.9976341,0.0003342712,0.0005776403,0.0002748064,0.001101578,0.00007763693],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002383503,0.0003149241,0.9419008,0.003250335,0.00003267062,0.00007577681,0.0001494153,0.000005774371,0.0000174879,0.0005659903,0.04039579,0.01090748],"study_design_scores_gemma":[0.001614739,0.003552528,0.9756194,0.003825137,0.0002629024,0.00002897101,0.00008575832,0.000003298466,0.000068511,0.000431008,0.01441974,0.00008795568],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9468107,0.0361201,0.0002836321,0.01252709,0.000588966,0.002579996,0.00002683446,0.0000132027,0.001049438],"genre_scores_gemma":[0.9808749,0.009431974,0.002583996,0.005744033,0.000820477,0.00005293417,0.00002606334,0.00002237006,0.0004432586],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03406415,"threshold_uncertainty_score":0.4899563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00758924052485853,"score_gpt":0.2575184104831144,"score_spread":0.2499291699582559,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}