{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008479256,0.0006772146,0.0008676308,0.001992636,0.001063181,0.002326019,0.001182681,0.002438061,0.04887318],"category_scores_gemma":[0.04131323,0.0004721842,0.0007865379,0.002795162,0.0006549234,0.001779423,0.002066274,0.003753095,0.004718707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004533002,"about_ca_system_score_gemma":0.01714177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05403426,"about_ca_topic_score_gemma":0.07520974,"domain_scores_codex":[0.995899,0.001770415,0.0002596022,0.0002019516,0.001504711,0.0003642888],"domain_scores_gemma":[0.9782282,0.007704085,0.001698824,0.001625592,0.005445116,0.005298187],"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":[0.00003710986,0.00008573673,0.003426454,0.00008736214,0.00002291336,0.00001069517,0.00001149256,0.0001479816,0.00001361568,0.00529562,0.9223069,0.06855413],"study_design_scores_gemma":[0.000650626,0.0001508015,0.06255808,0.001318824,0.0001716231,0.0001757417,0.0001167494,0.002014556,0.0001818244,0.01556347,0.9170352,0.00006247358],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.004537506,0.02950126,0.005256606,0.6748271,0.00813656,0.001039984,0.04095046,0.001165268,0.2345852],"genre_scores_gemma":[0.2256056,0.1828703,0.0989667,0.2107372,0.01601098,0.00599198,0.06413642,0.001256375,0.1944245],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.05403426,"threshold_uncertainty_score":0.1634971,"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."}}