{"id":"W4388913253","doi":"10.3758/s13428-023-02238-7","title":"Disaggregating level-specific effects in cross-classified multilevel models","year":2023,"lang":"en","type":"article","venue":"Behavior Research Methods","topic":"Mental Health Research Topics","field":"Psychology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Conflation; Multilevel model; Computer science; Cluster (spacecraft); Random effects model; Artificial intelligence; Machine learning; Meta-analysis; Linguistics","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":[0.01980375,0.001641469,0.002197738,0.001377192,0.00120657,0.003924864,0.004167594,0.002499797,0.007925529],"category_scores_gemma":[0.04832594,0.001060827,0.003883688,0.002328958,0.002011144,0.005163457,0.005013411,0.0061872,0.001686242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001973541,"about_ca_system_score_gemma":0.001834501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008359596,"about_ca_topic_score_gemma":0.0133016,"domain_scores_codex":[0.9862111,0.00971818,0.0005791385,0.002077355,0.0008330802,0.0005811488],"domain_scores_gemma":[0.9710972,0.0174224,0.002624678,0.006581138,0.001775086,0.0004993557],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005336762,0.0002529458,0.03804136,0.0006827864,0.001648081,0.0006194816,0.004777551,0.2018723,0.001668412,0.6374709,0.005951369,0.1064811],"study_design_scores_gemma":[0.00008754671,0.0002047654,0.007400197,0.0002959887,0.000541718,0.0001705418,0.0005495448,0.4431134,0.000934104,0.5329438,0.01363502,0.000123355],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03586404,0.0007017055,0.9580113,0.0008924124,0.000125056,0.000174066,0.0008609545,0.0005675814,0.002802883],"genre_scores_gemma":[0.5532051,0.0008497414,0.4364921,0.001083364,0.0001369434,0.0009955795,0.001910043,0.0004723073,0.004854703],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01980375,"threshold_uncertainty_score":0.1047335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8313128540076932,"score_gpt":0.7245869789737178,"score_spread":0.1067258750339753,"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."}}