{"id":"W2162742718","doi":"10.1093/her/cyg043","title":"Creating parsimony at the expense of precision? Conceptual and applied issues of aggregating belief-based constructs in physical activity research","year":2004,"lang":"en","type":"article","venue":"Health Education Research","topic":"Behavioral Health and Interventions","field":"Psychology","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Structural equation modeling; Scale (ratio); Psychology; Latent variable; Variance (accounting); Psychological intervention; Cognition; Social psychology; Physical activity; Latent variable model; Econometrics; Cognitive psychology; Mathematics; Statistics; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004581491,0.00009487834,0.0002848782,0.0003716669,0.0005168483,0.00001583384,0.0002037475,0.00009503612,0.000282743],"category_scores_gemma":[0.0005969342,0.00007791285,0.00003967312,0.0008831005,0.001349743,0.00005773016,0.0001112764,0.000807184,0.00002708336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003567311,"about_ca_system_score_gemma":0.002107202,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01708832,"about_ca_topic_score_gemma":0.00117179,"domain_scores_codex":[0.9960959,0.001708544,0.0004763943,0.0003652479,0.0007327465,0.0006211982],"domain_scores_gemma":[0.9964721,0.002102555,0.0002226123,0.0004565522,0.0005301313,0.0002161022],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001461548,0.007894776,0.04544684,0.0007982345,0.0000183745,0.000001879208,0.1028143,0.00004608291,0.004971509,0.07271592,0.006898326,0.7569322],"study_design_scores_gemma":[0.004424088,0.003230345,0.7902046,0.002336821,0.000007623894,0.000009937845,0.1579356,0.00009598919,0.03483113,0.004333206,0.002310264,0.00028031],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9896528,0.001327228,0.000006303433,0.005316499,0.0001280732,0.001414564,0.00002023584,0.000008506558,0.002125816],"genre_scores_gemma":[0.9985374,0.00004581822,0.0003896793,0.00006541294,0.0000830573,0.0004586009,0.00001250287,0.00001398312,0.0003935677],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7566519,"threshold_uncertainty_score":0.989457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3041000354369958,"score_gpt":0.5977252260886646,"score_spread":0.2936251906516689,"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."}}