{"id":"W1981766652","doi":"10.1080/00273171.2012.658328","title":"Modeling Individual Differences in Within-Person Variation of Negative and Positive Affect in a Mixed Effects Location Scale Model Using BUGS/JAGS","year":2012,"lang":"en","type":"article","venue":"Multivariate Behavioral Research","topic":"Mental Health Research Topics","field":"Psychology","cited_by":86,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Affect (linguistics); Stressor; Psychology; Mood; Multilevel model; Scale (ratio); Random effects model; Interaction; Correlation; Variation (astronomy); Developmental psychology; Statistics; Clinical psychology; Medicine; Mathematics; Meta-analysis","routes":{"ca_aff":true,"ca_fund":false,"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":[0.01300667,0.001847971,0.001798938,0.001687913,0.0007285356,0.001863134,0.003098774,0.001632879,0.006385068],"category_scores_gemma":[0.02209668,0.001191762,0.004999748,0.001503511,0.001087642,0.001037871,0.001671948,0.002104917,0.0009021544],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001092685,"about_ca_system_score_gemma":0.001140973,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0258795,"about_ca_topic_score_gemma":0.01441299,"domain_scores_codex":[0.9931606,0.004770215,0.0001829278,0.001178792,0.0003024876,0.00040496],"domain_scores_gemma":[0.9873236,0.00930804,0.0007734473,0.001422412,0.0008738583,0.0002987002],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.005085308,0.001708301,0.256745,0.0002975366,0.006090274,0.0009617006,0.002767286,0.6367834,0.004574325,0.02303387,0.004208022,0.05774509],"study_design_scores_gemma":[0.0002860398,0.001146615,0.02968878,0.00003504146,0.0005755929,0.0001159077,0.0002717378,0.9610896,0.0006230571,0.004034254,0.002063171,0.00007026969],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6663733,0.000211205,0.3281288,0.0003342776,0.0002335784,0.0008533762,0.001823199,0.0009722306,0.00107012],"genre_scores_gemma":[0.888557,0.000129185,0.1007582,0.0001161018,0.00005427704,0.002738673,0.001935748,0.0001401137,0.00557089],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0258795,"threshold_uncertainty_score":0.06878668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4533174597486033,"score_gpt":0.5344039001917903,"score_spread":0.08108644044318702,"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."}}