{"id":"W2738359971","doi":"10.1007/s10957-017-1139-7","title":"Optimal Timing to Initiate Medical Treatment for a Disease Evolving as a Semi-Markov Process","year":2017,"lang":"en","type":"article","venue":"Journal of Optimization Theory and Applications","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Theory of computation; Mathematics; Process (computing); Markov process; Markov decision process; Mathematical optimization; Markov chain; Calculus (dental); Applied mathematics; Computer science; Medicine; Algorithm; Statistics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.006225212,0.0008481899,0.002707089,0.0009595009,0.0004199036,0.001722224,0.001416348,0.002360441,0.006311074],"category_scores_gemma":[0.0277198,0.0009002523,0.001203676,0.0006539,0.001405999,0.001873022,0.001141621,0.003410122,0.0005784329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001315514,"about_ca_system_score_gemma":0.003802635,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002650081,"about_ca_topic_score_gemma":0.00179609,"domain_scores_codex":[0.9977718,0.001077363,0.0001344912,0.0004656973,0.0002314426,0.0003191262],"domain_scores_gemma":[0.9649017,0.03064558,0.002154128,0.0005018489,0.0006218686,0.00117501],"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":[0.003637925,0.0006544915,0.01396749,0.0004742405,0.0005094549,0.0005351921,0.0002210833,0.687555,0.003448039,0.2301951,0.005607508,0.05319444],"study_design_scores_gemma":[0.0005128458,0.0007028441,0.003135774,0.0001025727,0.0003097068,0.0002131111,0.0000711079,0.8908663,0.001076167,0.1018871,0.001061627,0.00006088502],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3175856,0.002375389,0.6558781,0.01501254,0.0005763813,0.0004721031,0.001503763,0.0004785981,0.006117508],"genre_scores_gemma":[0.9496077,0.001165299,0.04192746,0.0007198817,0.0004093673,0.0003635208,0.0005509743,0.00005448988,0.005201383],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006311074,"threshold_uncertainty_score":0.03292245,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2880180947609726,"score_gpt":0.5617737587265674,"score_spread":0.2737556639655948,"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."}}