{"id":"W4413098862","doi":"10.3332/ecancer.2025.1953","title":"Unlocking artificial intelligence, machine learning and deep learning to combat therapeutic resistance in metastatic castration-resistant prostate cancer: a comprehensive review","year":2025,"lang":"en","type":"review","venue":"ecancermedicalscience","topic":"Prostate Cancer Treatment and Research","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Medicine; Prostate cancer; Artificial intelligence; Deep learning; Cancer; Internal medicine; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.000782546,0.0006220713,0.001070908,0.001790336,0.0001855177,0.0009798659,0.0005746901,0.0009501681,0.003128457],"category_scores_gemma":[0.001390606,0.0002328224,0.0006626946,0.00142469,0.0003130996,0.001083901,0.0006271166,0.001476076,0.001093462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004454322,"about_ca_system_score_gemma":0.00126411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009956724,"about_ca_topic_score_gemma":0.002232207,"domain_scores_codex":[0.9997948,0.00004882089,0.00003310527,0.00003384602,0.00006970193,0.0000197652],"domain_scores_gemma":[0.9993369,0.0004642499,0.00005725664,0.00001263836,0.0001017889,0.00002719896],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004632823,0.00005152499,0.0001285911,0.02920207,0.0001615753,0.00008693885,0.00006943107,0.0005564617,0.0008554607,0.004568516,0.01671895,0.9475543],"study_design_scores_gemma":[0.00002436677,0.0002266528,0.0007442252,0.01443486,0.0003676297,0.0006144955,0.00008419154,0.0003479938,0.0005377014,0.004253477,0.9783329,0.00003147955],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001190106,0.998456,0.0002197375,0.000395682,0.0001177391,0.000007104918,0.00001916808,0.000008051188,0.0006575192],"genre_scores_gemma":[0.0007372591,0.9983816,0.0002687952,0.0002351482,0.0001008017,0.000007886509,0.00002355833,0.000001803559,0.0002431433],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003128457,"threshold_uncertainty_score":0.0104658,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08354280092565135,"score_gpt":0.4314013610721022,"score_spread":0.3478585601464508,"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."}}