{"id":"W3015442555","doi":"10.1038/s41409-020-0871-z","title":"Precision medicine: Statistical methods for estimating adaptive treatment strategies","year":2020,"lang":"en","type":"editorial","venue":"Bone Marrow Transplantation","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"National Cancer Institute; National Heart, Lung, and Blood Institute; Canadian Institutes of Health Research; National Institutes of Health","keywords":"Precision medicine; Marketing buzz; Computer science; Replicate; Point (geometry); Statistics; Medicine; Operations research; Mathematics; Pathology","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":[0.05000929,0.007988331,0.01094914,0.008578106,0.002960462,0.01233751,0.00823011,0.03524232,0.01392463],"category_scores_gemma":[0.2059719,0.00389631,0.0068752,0.005772677,0.009871569,0.008001117,0.003453852,0.0421568,0.01070066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006057755,"about_ca_system_score_gemma":0.00707848,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004644579,"about_ca_topic_score_gemma":0.008064997,"domain_scores_codex":[0.9587716,0.02314953,0.004432132,0.002679034,0.0103873,0.0005804597],"domain_scores_gemma":[0.7425434,0.2067218,0.005422353,0.005984196,0.03500883,0.004319506],"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":[0.00005659816,0.0000126593,0.00001771569,0.0005954124,0.0001150409,0.00003165506,0.00001215869,0.000135346,0.00002140082,0.001152734,0.9907065,0.007142776],"study_design_scores_gemma":[0.0008718882,0.000101291,0.0005624209,0.003278476,0.0007210266,0.0004571819,0.00005547423,0.003889281,0.0002603167,0.03492662,0.9546573,0.0002188813],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00001830666,0.02846124,0.004253598,0.0561775,0.9100186,0.00003975603,0.0001856754,0.0002568423,0.0005884976],"genre_scores_gemma":[0.0003615662,0.008836123,0.00198449,0.02683441,0.9587252,0.00009057448,0.00005882586,0.0001947071,0.002914107],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.05000929,"threshold_uncertainty_score":0.2644776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3506320034484279,"score_gpt":0.5732529388532968,"score_spread":0.2226209354048688,"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."}}