{"id":"W7085205598","doi":"10.6084/m9.figshare.30291991","title":"Additional file 4 of Machine learning-based radiomics using magnetic resonance images for prediction of clinical complete response to neoadjuvant chemotherapy in patients with muscle-invasive bladder cancer","year":2025,"lang":"en","type":"dataset","venue":"Figshare","topic":"Polar Research and Ecology","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Radiomics; Magnetic resonance imaging; Bladder cancer; Chemotherapy; Complete response; Patient data","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001054151,0.00204461,0.001839354,0.002147498,0.0006306505,0.002152516,0.002574051,0.002524005,0.4782818],"category_scores_gemma":[0.01153624,0.0006942482,0.002288062,0.002514834,0.0004337938,0.001274191,0.001354538,0.001491933,0.1136634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001350933,"about_ca_system_score_gemma":0.001871271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01303465,"about_ca_topic_score_gemma":0.02269995,"domain_scores_codex":[0.9993268,0.00008965402,0.0001083194,0.000262232,0.0000986833,0.0001144077],"domain_scores_gemma":[0.9948751,0.003210507,0.0004488523,0.0005182955,0.0006969033,0.000250247],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008099675,0.000154226,0.005945896,0.003622478,0.0002559837,0.00009287319,0.00004686612,0.001057357,0.0002330654,0.0004314317,0.9802716,0.007078203],"study_design_scores_gemma":[0.011691,0.000437576,0.06142734,0.00382168,0.001016948,0.0008101552,0.0003629145,0.005768734,0.001748677,0.01177513,0.9008399,0.0003000329],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001444055,0.00002448411,0.00004842563,0.00003938719,0.00001414152,0.00001718337,0.9994784,0.00008494013,0.0001486837],"genre_scores_gemma":[0.002493145,0.00007282503,0.00076009,0.0001498548,0.00003868785,0.000474887,0.9942923,0.0001439427,0.001574264],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4782818,"threshold_uncertainty_score":0.7441677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03104781928991037,"score_gpt":0.2988692661759332,"score_spread":0.2678214468860228,"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."}}