{"id":"W4205276371","doi":"10.1371/journal.pone.0262407","title":"Predictors of perceived success in quitting smoking by vaping: A machine learning approach","year":2022,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Smoking Behavior and Cessation","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Children's Hospital of Eastern Ontario; Ontario Tobacco Research Unit; Public Health Ontario; University of Toronto","funders":"Ontario Ministry of Health and Long-Term Care","keywords":"Smoking cessation; Receiver operating characteristic; Confidence interval; Medicine; Young adult; Demography; Nicotine; Quit smoking; Boosting (machine learning); Cigarette smoking; Cross-sectional study; Machine learning; Internal medicine; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.003903917,0.0008520221,0.0008338296,0.003096775,0.0004475701,0.001400355,0.0008828238,0.0008412705,0.00114919],"category_scores_gemma":[0.01160748,0.0003502073,0.001297639,0.00166853,0.0004936278,0.0007283016,0.0006854113,0.001626985,0.000286238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005982,"about_ca_system_score_gemma":0.0008239207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008313639,"about_ca_topic_score_gemma":0.00494923,"domain_scores_codex":[0.9988589,0.000612511,0.00008839833,0.0001650541,0.0001421389,0.000132978],"domain_scores_gemma":[0.9930751,0.005215388,0.0007481165,0.0002181772,0.000448883,0.0002942844],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002681809,0.0005878095,0.9439567,0.00008060186,0.0004327577,0.0001234079,0.0002703115,0.01848683,0.0004468217,0.0003346168,0.0005341058,0.03447789],"study_design_scores_gemma":[0.00004355537,0.0005353905,0.4192769,0.00009610632,0.0001998483,0.0001801236,0.0004234216,0.576348,0.0003273022,0.0021746,0.0003486918,0.00004608558],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9843832,0.0006668959,0.0130285,0.0006102525,0.00002676768,0.0000856418,0.0004070799,0.00009516023,0.0006966086],"genre_scores_gemma":[0.9950734,0.0001204228,0.004327167,0.00003119507,0.00002710006,0.00003602679,0.0002525364,0.000003385687,0.0001288453],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008313639,"threshold_uncertainty_score":0.0206461,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04879287669631645,"score_gpt":0.2591580659139001,"score_spread":0.2103651892175836,"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."}}