{"id":"W2983958955","doi":"10.1093/ntr/ntz211","title":"Toward Precision Medicine for Smoking Cessation: Developing a Neuroimaging-Based Classification Algorithm to Identify Smokers at Higher Risk for Relapse","year":2019,"lang":"en","type":"article","venue":"Nicotine & Tobacco Research","topic":"Smoking Behavior and Cessation","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"National Cancer Institute; National Institute on Drug Abuse; Canadian Institutes of Health Research; National Institutes of Health","keywords":"Abstinence; Neuroimaging; Smoking cessation; Addiction; Medicine; Clinical psychology; Discriminant function analysis; Psychological intervention; Psychiatry; Psychology; Algorithm; Internal medicine; Machine learning; Pathology; Computer science","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":[0.007110355,0.001203466,0.001775209,0.004326039,0.0007375168,0.002650909,0.001496559,0.002164732,0.001892606],"category_scores_gemma":[0.01601702,0.0003508381,0.001357932,0.001376992,0.000776962,0.001229623,0.0008001614,0.001853527,0.0009970195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001147273,"about_ca_system_score_gemma":0.001702353,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003171347,"about_ca_topic_score_gemma":0.001954851,"domain_scores_codex":[0.9982631,0.0006849216,0.0001766721,0.0004655803,0.000298413,0.0001112953],"domain_scores_gemma":[0.9926503,0.005004814,0.0007522325,0.0003716716,0.001042852,0.0001780285],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001111337,0.0008412232,0.2033474,0.0004224395,0.0007578627,0.0001997275,0.0002552068,0.06163146,0.007363216,0.003460736,0.007514843,0.7130946],"study_design_scores_gemma":[0.0002054709,0.0005011483,0.04018799,0.0004279066,0.0003690587,0.0004382447,0.0001806048,0.9280424,0.005482791,0.0209477,0.003127446,0.00008915928],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2178629,0.005373991,0.7629883,0.005731278,0.0002703617,0.0006503394,0.001214315,0.002850858,0.003057737],"genre_scores_gemma":[0.6349311,0.0007918187,0.3605264,0.000957539,0.0002683575,0.0004886569,0.001122408,0.00007731646,0.0008364213],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007110355,"threshold_uncertainty_score":0.03760362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2026959532891117,"score_gpt":0.4536947394812851,"score_spread":0.2509987861921734,"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."}}