{"id":"W7085186077","doi":"10.6084/m9.figshare.30291997","title":"Additional file 6 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":"HIV/AIDS Research and Interventions","field":"Medicine","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":[0.001321698,0.002257821,0.002079015,0.002267132,0.0006490811,0.002235697,0.002842735,0.002893096,0.4231144],"category_scores_gemma":[0.01354977,0.0008266931,0.002836314,0.002614937,0.0004796997,0.001314431,0.001381288,0.001725797,0.1135349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001469465,"about_ca_system_score_gemma":0.002055616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01516453,"about_ca_topic_score_gemma":0.02541783,"domain_scores_codex":[0.9991506,0.0001425512,0.0001391011,0.0003206757,0.0001149349,0.0001320747],"domain_scores_gemma":[0.9936213,0.003973217,0.000595394,0.0007079435,0.0007927355,0.0003093307],"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":[0.0008373753,0.0001640044,0.005613083,0.003757651,0.0003139329,0.00007510458,0.00003822914,0.001046938,0.0001675553,0.0004118126,0.9815423,0.006032099],"study_design_scores_gemma":[0.01632081,0.0005224524,0.06269264,0.004260352,0.001319502,0.0007164238,0.0003535118,0.006457566,0.001559978,0.01104635,0.8944252,0.0003251304],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001365046,0.00002759699,0.00004230329,0.00005041465,0.00001375093,0.00001902002,0.9994887,0.00008354225,0.000138048],"genre_scores_gemma":[0.002133825,0.0000757864,0.0006817987,0.0001685055,0.00003833335,0.0005175087,0.9948342,0.0001146392,0.001435459],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4231144,"threshold_uncertainty_score":0.8228574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04575453507088394,"score_gpt":0.3513181990958625,"score_spread":0.3055636640249785,"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."}}