{"id":"W2234693855","doi":"","title":"A NOTE OF CAUTION ON COVARIANCE - EQUIVALENT MODELS IN INFORMATION SYSTEMS","year":2012,"lang":"en","type":"article","venue":"","topic":"Technology Adoption and User Behaviour","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Covariance; Structural equation modeling; Causal model; Computer science; Econometrics; Statistical hypothesis testing; Statistical model; Analysis of covariance; Mathematics; Machine learning; Statistics","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1678852,0.002341313,0.004714817,0.003489591,0.00551599,0.01202282,0.01867574,0.01606505,0.006507524],"category_scores_gemma":[0.3650011,0.001780305,0.006060489,0.005834092,0.02237736,0.02014536,0.007521761,0.0594239,0.006140606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00502844,"about_ca_system_score_gemma":0.009742428,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01967979,"about_ca_topic_score_gemma":0.02939443,"domain_scores_codex":[0.8361109,0.1110232,0.0153362,0.01170431,0.02409071,0.001734808],"domain_scores_gemma":[0.5310103,0.3823424,0.01127796,0.0299709,0.04213996,0.003258466],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001829492,0.000103134,0.003282869,0.001851224,0.0005200061,0.000974912,0.008032293,0.003199523,0.0003617577,0.4842299,0.4619808,0.03528056],"study_design_scores_gemma":[0.0001127183,0.0001100126,0.002454641,0.003448058,0.0001744786,0.001020125,0.002857133,0.01073905,0.0006498102,0.6767383,0.3013844,0.0003113331],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"methods","genre_scores_codex":[0.003449666,0.01454029,0.09006635,0.8436661,0.03311759,0.0002241231,0.001685853,0.0008176314,0.01243245],"genre_scores_gemma":[0.1520025,0.01550503,0.209048,0.5395615,0.05479536,0.001743393,0.0007986579,0.001171158,0.02537445],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8321148,"threshold_uncertainty_score":0.8878723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1686482008288641,"score_gpt":0.3941068780173167,"score_spread":0.2254586771884526,"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."}}