{"id":"W2925324768","doi":"10.1002/cjs.11492","title":"Linear mode regression with covariate measurement error","year":2019,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Covariate; Estimator; Statistics; Observational error; Mathematics; Inference; Regression analysis; Linear regression; Regression; Statistical inference; Errors-in-variables models; Econometrics; Computer science; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006893955,0.0001403534,0.0003289728,0.0001223571,0.00006952917,0.00003744326,0.0001812467,0.000056928,0.0008689144],"category_scores_gemma":[0.001823297,0.0000953941,0.00003099719,0.0001055972,0.00007644147,0.00005382155,0.000007230081,0.0002796298,0.000020303],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001843036,"about_ca_system_score_gemma":0.001529599,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009171978,"about_ca_topic_score_gemma":0.004644962,"domain_scores_codex":[0.9985986,0.0001003857,0.0004282281,0.0001091076,0.0004821866,0.0002815306],"domain_scores_gemma":[0.9976419,0.0004069279,0.0003409261,0.0001933748,0.0008539734,0.0005629],"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":[0.0001948268,0.00007021903,0.005981678,0.0003452019,0.0002192127,0.0007799513,0.001122795,0.0003602499,0.0004770244,0.9373224,0.03169343,0.02143298],"study_design_scores_gemma":[0.002740093,0.002157584,0.006901421,0.001968182,0.0003677108,0.000409267,0.000525105,0.031926,0.0006825075,0.940303,0.01125842,0.0007606708],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01292061,0.00005777618,0.984427,0.0002107814,0.0004227854,0.0001400511,0.0003442217,0.000005121397,0.001471671],"genre_scores_gemma":[0.3181604,0.00000478354,0.681482,0.00009599775,0.00006477401,8.230303e-7,0.000001802435,0.00002113968,0.0001683257],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3052398,"threshold_uncertainty_score":0.9514004,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1847865007814968,"score_gpt":0.3546108172006761,"score_spread":0.1698243164191793,"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."}}