{"id":"W2087713388","doi":"10.2333/bhmk.32.141","title":"An Extended Multivariate Random-Effects Growth Curve Model","year":2005,"lang":"en","type":"article","venue":"Behaviormetrika","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; HEC Montréal","funders":"","keywords":"Growth curve (statistics); Multivariate statistics; Random effects model; Mathematics; Statistics; A priori and a posteriori; Multivariate analysis; Basis (linear algebra); Set (abstract data type); Econometrics; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007613187,0.0002791829,0.0004750915,0.0002172567,0.000131153,0.00008221578,0.0003215296,0.0001670406,0.0002046403],"category_scores_gemma":[0.002114699,0.0002329687,0.0001254473,0.0003870354,0.00007524055,0.0002909038,0.00005186129,0.0002735112,0.00005583522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007740724,"about_ca_system_score_gemma":0.0000576004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005728289,"about_ca_topic_score_gemma":0.00001422707,"domain_scores_codex":[0.9980085,0.0002700453,0.000446376,0.0004216776,0.0003881924,0.0004651913],"domain_scores_gemma":[0.9975021,0.001443572,0.0001386307,0.0004937564,0.0001440985,0.0002777766],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000194261,0.001904562,0.00125155,0.0001096713,0.00003009941,0.00003926698,0.0005320224,0.000008460229,0.01110807,0.5739001,0.0007348803,0.410187],"study_design_scores_gemma":[0.006401844,0.0004538363,0.01833621,0.00009565086,0.0004001913,0.00002429522,0.00003752379,0.09152854,0.0280519,0.8536771,0.00008939331,0.0009035211],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06664111,0.00003656031,0.9312104,0.00004923074,0.0001212749,0.0005025681,0.0000603315,0.0002102621,0.001168241],"genre_scores_gemma":[0.4376946,0.000006659621,0.5619537,0.0000618341,0.00008325071,0.00006464226,0.0000064723,0.0000303824,0.00009847118],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4092835,"threshold_uncertainty_score":0.9500186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07029329654236934,"score_gpt":0.408737113280925,"score_spread":0.3384438167385557,"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."}}