{"id":"W4399919157","doi":"10.1002/adaw.34168","title":"NIDA's DTMC: Improving treatment and medical consequences","year":2024,"lang":"en","type":"article","venue":"Alcoholism & Drug Abuse Weekly","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Psychology; Computer science; Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.007529697,0.0003074557,0.0009144214,0.0003800422,0.0002438084,0.0003526068,0.0002817037,0.000208188,0.0008830816],"category_scores_gemma":[0.001052809,0.0003268438,0.0001523689,0.0002143839,0.0002995427,0.0005886548,0.00005536446,0.0002419045,0.002672664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004859176,"about_ca_system_score_gemma":0.0004088416,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005531403,"about_ca_topic_score_gemma":0.0005544566,"domain_scores_codex":[0.9956548,0.0002332978,0.002501786,0.0009055799,0.0001553587,0.0005491724],"domain_scores_gemma":[0.9971743,0.001350081,0.0005196459,0.0004732611,0.00003403469,0.0004486608],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000516875,0.0004784387,0.04276603,0.002007777,0.001126635,0.0002844965,0.05661327,0.00006421588,0.0001400195,0.6978623,0.1674967,0.03110836],"study_design_scores_gemma":[0.003140039,0.0003304652,0.01134807,0.0009353129,0.0001079929,0.0003037817,0.006090944,0.02868035,0.000177557,0.04150246,0.9055874,0.001795587],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8615386,0.02800103,0.000469459,0.1012527,0.001827588,0.0006557553,0.0002168991,0.0002944657,0.005743449],"genre_scores_gemma":[0.9852148,0.002682287,0.0007447862,0.006730638,0.0009216001,0.0001697129,0.00003252921,0.00006173536,0.003441946],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7380907,"threshold_uncertainty_score":0.9999183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1813054716062532,"score_gpt":0.4024667987424936,"score_spread":0.2211613271362404,"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."}}