{"id":"W6889073132","doi":"10.25384/sage.c.5291538","title":"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":"other","venue":"Sage Journals Data","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Latent class model; Multilevel model; Longitudinal data; Longitudinal study; Sample (material); Class (philosophy); Scale (ratio); Mixture model","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":[0.001417538,0.000449785,0.001208704,0.006537937,0.00003803643,0.0001401987,0.001915269,0.0003779737,0.01461398],"category_scores_gemma":[0.0003741867,0.0004694296,0.0001908518,0.002855053,0.00004375335,0.0003601348,0.0005229095,0.0005276108,0.00007078169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003522764,"about_ca_system_score_gemma":0.0008446656,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9066531,"about_ca_topic_score_gemma":0.9835492,"domain_scores_codex":[0.995644,0.0005342648,0.001276482,0.001022775,0.0009032324,0.0006192524],"domain_scores_gemma":[0.9935551,0.00006002066,0.001589682,0.003880537,0.0002420117,0.0006726512],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00032582,0.002560328,0.8456602,0.001243702,0.01489908,0.0004912658,0.007052505,0.006233936,0.0439936,0.00001501758,0.04919367,0.02833086],"study_design_scores_gemma":[0.008440955,0.0003120277,0.7181029,0.02538037,0.01310713,0.00002958373,0.008199999,0.04188739,0.004041518,0.00002369534,0.1755684,0.004906126],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.01332615,0.00160602,0.01540223,0.00004615296,0.0001249876,0.002038596,0.9663489,0.00004545492,0.001061428],"genre_scores_gemma":[0.6463661,0.003187142,0.02931777,0.0002627234,0.0007361012,0.0002355127,0.2856246,0.002642208,0.0316279],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.6807244,"threshold_uncertainty_score":0.9997758,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1881875354976725,"score_gpt":0.3629932354281015,"score_spread":0.174805699930429,"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."}}