{"id":"W4382989916","doi":"10.3390/books978-3-0365-7908-5","title":"Cancer Prevention with Molecular Target Therapies 3.0","year":2023,"lang":"en","type":"book","venue":"","topic":"Advanced Breast Cancer Therapies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Deutsche Gesellschaft für Urologie; Astellas Pharma; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Canadian Dermatology Foundation; Japan Society for the Promotion of Science; Ministerstvo Školství, Mládeže a Tělovýchovy; AstraZeneca; Bristol-Myers Squibb; Universität Heidelberg; Pfizer; National Science Foundation","keywords":"Cancer; Medicine; Internal medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004876786,0.0009824506,0.0005568025,0.001452823,0.0004993013,0.002966958,0.0008814621,0.001743031,0.1050833],"category_scores_gemma":[0.0006788902,0.0003545952,0.0007883951,0.0008405834,0.0009213305,0.002314003,0.00140205,0.003208229,0.07305345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001136192,"about_ca_system_score_gemma":0.0009033857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000909594,"about_ca_topic_score_gemma":0.002158875,"domain_scores_codex":[0.9996427,0.00006118797,0.00001313011,0.00004276354,0.0002188526,0.00002124422],"domain_scores_gemma":[0.9997198,0.0001085804,0.00002035055,0.00003369952,0.00006978102,0.00004769957],"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":[0.00004195923,0.00005978655,0.0000477371,0.0007137615,0.00001206899,0.00008939726,0.00009028911,0.0002700239,0.001985567,0.05005294,0.6584278,0.2882087],"study_design_scores_gemma":[0.000003638968,0.000009879268,0.00003177676,0.0001078622,0.000002189775,0.0001513344,0.00000798121,0.00006087215,0.0001803457,0.005103539,0.994337,0.000003516302],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00055147,0.1554958,0.0132015,0.01753021,0.01473995,0.000143457,0.0006513334,0.002026296,0.79566],"genre_scores_gemma":[0.003120502,0.09089302,0.01264031,0.01306812,0.005327858,0.000123273,0.0004505899,0.0006308925,0.8737455],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1050833,"threshold_uncertainty_score":0.3515386,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01507194981185289,"score_gpt":0.2978450724852088,"score_spread":0.2827731226733559,"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."}}