{"id":"W4386807108","doi":"10.1101/2023.09.14.23295596","title":"ReMIND: The Brain Resection Multimodal Imaging Database","year":2023,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"National Institutes of Health; Brigham and Women's Hospital","keywords":"Resection; Computer science; Database; Medicine; Surgery","routes":{"ca_aff":true,"ca_fund":false,"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":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.002636024,0.0002952807,0.0004118866,0.0002314487,0.0002225172,0.0000988849,0.0004274586,0.00014943,0.0001051728],"category_scores_gemma":[0.004409751,0.0002030235,0.0002153305,0.0002294991,0.0002165741,0.00004909721,0.0008602253,0.003043062,0.0001638511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001127204,"about_ca_system_score_gemma":0.0001953768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008042348,"about_ca_topic_score_gemma":0.0000320404,"domain_scores_codex":[0.9975681,0.0002195144,0.0004299694,0.0007204081,0.0006330723,0.0004288962],"domain_scores_gemma":[0.9977025,0.0005484745,0.0001981782,0.001239618,0.00009799351,0.0002132013],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004796166,0.0002901615,0.5306299,0.002169007,0.0006028343,0.002795041,0.002618644,0.001825729,0.04531558,0.0004571019,0.3166073,0.09620907],"study_design_scores_gemma":[0.002534658,0.00008805936,0.2405554,0.003152489,0.000498505,0.0005480886,0.0004551995,0.6180056,0.001700918,0.002118045,0.1295271,0.0008159516],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7942648,0.0009002593,0.01332611,0.1812621,0.005231788,0.001147436,0.00004961235,0.000739644,0.003078277],"genre_scores_gemma":[0.9783022,0.0003342231,0.003801397,0.004981012,0.003212184,0.0001470603,0.0006327214,0.0002054821,0.008383703],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6161799,"threshold_uncertainty_score":0.999257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03019763176483569,"score_gpt":0.3404068865910313,"score_spread":0.3102092548261956,"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."}}