{"id":"W1977806117","doi":"10.1098/rsta.2010.0220","title":"Piecewise affine systems modelling for optimizing hormone therapy of prostate cancer","year":2010,"lang":"en","type":"article","venue":"Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences","topic":"Prostate Cancer Treatment and Research","field":"Medicine","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver General Hospital","funders":"","keywords":"Prostate cancer; Androgen suppression; Medicine; Androgen; Computer science; Hormone therapy; Disease; Androgen deprivation therapy; Cancer; Hormone; Oncology; Internal medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.0001944706,0.0001185264,0.0003066922,0.00001996665,0.0001477148,0.00001704272,0.0001203865,0.00005709497,0.000005526208],"category_scores_gemma":[0.00001649773,0.00006469159,0.0002586639,0.0002120335,0.0005010407,0.00005615782,0.00001166433,0.0002481576,1.803979e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001235002,"about_ca_system_score_gemma":0.00004465615,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001791487,"about_ca_topic_score_gemma":7.14106e-8,"domain_scores_codex":[0.9991369,0.000006537995,0.0001917901,0.0001709896,0.0002922922,0.000201512],"domain_scores_gemma":[0.9994589,0.0002090588,0.0000438563,0.0001196869,0.00007518225,0.00009329683],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003415843,0.001617781,0.00005977683,0.002155218,0.0005112909,4.559714e-7,0.002614364,0.7869096,0.1678995,0.03516951,0.00001964631,0.00270127],"study_design_scores_gemma":[0.0007537538,0.0002771359,0.00005208916,0.0001562371,0.00006584787,0.000001795719,0.00004968768,0.9785702,0.008056528,0.01191485,0.00002056111,0.00008133583],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.928023,0.0008795485,0.06531923,0.004750171,0.00009750595,0.0007569548,0.00004094288,0.00003606558,0.00009662352],"genre_scores_gemma":[0.9917017,0.0002253451,0.007771567,0.000008639957,0.0001136204,0.0001091626,5.590337e-7,0.00001076894,0.00005866964],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1916606,"threshold_uncertainty_score":0.2638046,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03909653041736443,"score_gpt":0.2923685408968031,"score_spread":0.2532720104794387,"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."}}