{"id":"W6963929064","doi":"10.25384/sage.13708932.v1","title":"Supplemental Material, sj-bib-1-ehp-10.1177_0163278721989547 - Multilevel Latent Class Profile Analysis: An Application to Stage-Sequential Patterns of Alcohol Use in a Sample of Canadian Youth","year":2021,"lang":"en","type":"dataset","venue":"Sage Journals Data","topic":"Ecology and biodiversity studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Latent class model; Sample (material); Multilevel model; Class (philosophy); Alcohol consumption; Scale (ratio)","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":[0.002037921,0.00139308,0.001120687,0.003027919,0.001829534,0.002613728,0.003465093,0.001773911,0.2020211],"category_scores_gemma":[0.01356899,0.001014463,0.001260806,0.005425693,0.0004998249,0.000880798,0.002275347,0.001622782,0.09010536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007356989,"about_ca_system_score_gemma":0.01562177,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6963528,"about_ca_topic_score_gemma":0.8546645,"domain_scores_codex":[0.9988304,0.0001437912,0.0001177621,0.0002455903,0.0003847377,0.0002778031],"domain_scores_gemma":[0.9936971,0.001485719,0.0003624214,0.0009001814,0.002816004,0.0007386385],"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":[0.0000334779,0.00001783208,0.001709064,0.0001709673,0.00001999274,0.000009023061,0.00002618527,0.0001292889,0.00002838462,0.000216051,0.99593,0.001709734],"study_design_scores_gemma":[0.0007246407,0.00002253122,0.03279406,0.000477786,0.00007424896,0.00005121403,0.0002265817,0.0006414092,0.0003313367,0.001599343,0.9629787,0.00007815823],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001016503,0.00001429418,0.00005529985,0.00004349759,0.00001080908,0.00002072558,0.9991848,0.0001694552,0.0003994778],"genre_scores_gemma":[0.0007527265,0.00002655272,0.0006357557,0.00006009082,0.000008261373,0.0002196725,0.9964707,0.0001237875,0.001702441],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3036472,"threshold_uncertainty_score":0.675828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09985740055247871,"score_gpt":0.3083322893967839,"score_spread":0.2084748888443052,"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."}}