{"id":"W2289119748","doi":"10.14288/1.0102112","title":"Covariance analysis of multiple linear regression equations","year":2011,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Proper linear model; Linear regression; Covariance; Regression analysis; Analysis of covariance; Mathematics; Statistics; Linear model; General linear model; Regression; Bayesian multivariate linear regression; Applied mathematics; Econometrics","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":[0.000217831,0.00003195191,0.0003546541,0.00006452357,0.0001022758,0.000005489335,0.0001761561,0.00006219088,0.0001950572],"category_scores_gemma":[0.0006139023,0.00009600703,0.0001462405,0.0004948314,0.0001737557,0.0001336994,0.00007023331,0.00008174668,0.000002271746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000192654,"about_ca_system_score_gemma":0.00002876547,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01473556,"about_ca_topic_score_gemma":0.0605107,"domain_scores_codex":[0.9992491,0.0000768793,0.0001643862,0.0002166052,0.0001650457,0.0001279743],"domain_scores_gemma":[0.9987113,0.0004790102,0.0002200743,0.0002757402,0.0002406032,0.00007322258],"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":[0.00005056936,0.0007050111,0.007033271,0.000234181,0.0005937565,0.00005678485,0.001471747,0.0001276064,0.0007212033,0.003368212,0.0004212649,0.9852164],"study_design_scores_gemma":[0.0008669739,0.00008215137,0.8249196,0.0002281991,0.001108989,0.000002406073,0.0007612297,0.04894906,0.0000132967,0.1227803,0.00006593089,0.0002218505],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2456577,0.00003220513,0.753289,0.000004001649,0.00003083739,0.00009327389,0.0002912421,0.0000227546,0.0005789775],"genre_scores_gemma":[0.6077892,0.0000288225,0.3919823,0.00000278178,0.000003934986,2.339185e-7,0.000008261747,0.000005248764,0.0001792736],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9849945,"threshold_uncertainty_score":0.9918254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.104459410478088,"score_gpt":0.3067267080694501,"score_spread":0.2022672975913621,"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."}}