{"id":"W2134792407","doi":"10.1186/1471-2288-12-159","title":"Should researchers use single indicators, best indicators, or multiple indicators in structural equation models?","year":2012,"lang":"en","type":"article","venue":"BMC Medical Research Methodology","topic":"Psychometric Methodologies and Testing","field":"Decision Sciences","cited_by":422,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Structural equation modeling; Latent variable; Path analysis (statistics); Econometrics; Computer science; Statistical model; Performance indicator; Confounding; Statistics; Risk analysis (engineering); Mathematics; Machine learning; Medicine; Economics","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":["metaresearch","metaepi_narrow","bibliometrics","research_integrity","insufficient_payload"],"consensus_categories":["metaresearch","bibliometrics","research_integrity"],"category_scores_codex":[0.2797406,0.0004901982,0.001607435,0.0191726,0.0005554737,0.0003809817,0.004226325,0.001549289,0.003893149],"category_scores_gemma":[0.9326814,0.0003258387,0.0002936981,0.02976135,0.002644595,0.001624047,0.002337086,0.004276934,0.000191823],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006479849,"about_ca_system_score_gemma":0.002590837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001530983,"about_ca_topic_score_gemma":0.001156232,"domain_scores_codex":[0.900068,0.07724222,0.002924924,0.001847331,0.01405228,0.003865181],"domain_scores_gemma":[0.1953667,0.7965987,0.001039673,0.002414043,0.0007218213,0.0038591],"domain_codex":null,"domain_gemma":"methods","domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006298674,0.0002954572,0.6568246,0.00003779817,0.00003448917,0.00004976792,0.001497525,0.00007872343,0.0001791988,0.005745786,0.00139521,0.3332315],"study_design_scores_gemma":[0.007153624,0.002405596,0.751096,0.0004744467,0.00005748705,0.0002498536,0.02222594,0.06022914,0.002670245,0.1026196,0.04893985,0.001878299],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8312503,0.001724994,0.1612789,0.001047739,0.001303451,0.0009707824,0.00002700877,0.0001106884,0.002286045],"genre_scores_gemma":[0.7845387,0.0003049903,0.2131133,0.0002796279,0.0006282906,0.0001609766,0.00002340782,0.00006083049,0.0008898939],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7193565,"threshold_uncertainty_score":0.9999194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9615285550475937,"score_gpt":0.6606017935692375,"score_spread":0.3009267614783562,"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."}}