{"id":"W3133814030","doi":"10.1080/03610926.2021.1890125","title":"Linear approximate Bayes estimator for regression parameter with an inequality constraint","year":2021,"lang":"en","type":"article","venue":"Communication in Statistics- Theory and Methods","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Mathematics; Estimator; Bayes' theorem; Applied mathematics; Constraint (computer-aided design); Mean squared error; Linear regression; Statistics; Bayesian probability","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":[],"consensus_categories":[],"category_scores_codex":[0.00345343,0.0009233473,0.001698761,0.0009441957,0.0004910806,0.001320505,0.001647044,0.001228527,0.00350358],"category_scores_gemma":[0.01505835,0.0005041021,0.0007738906,0.001083242,0.0008978068,0.001955831,0.001115965,0.001799609,0.001200661],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006415237,"about_ca_system_score_gemma":0.001636888,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004033204,"about_ca_topic_score_gemma":0.002600242,"domain_scores_codex":[0.9967777,0.001651697,0.0001386349,0.0005397329,0.0007276668,0.0001645538],"domain_scores_gemma":[0.9960968,0.002662814,0.0003014323,0.0002843,0.0006049781,0.00004957337],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003237953,0.0001288881,0.004553394,0.0007759942,0.0003166306,0.0003872216,0.0002057302,0.5078085,0.01273131,0.1672364,0.006000268,0.2995317],"study_design_scores_gemma":[0.00002406711,0.00003846464,0.0003884774,0.00004596266,0.00003664673,0.0001320613,0.00001854753,0.9713017,0.001779134,0.0244389,0.001775287,0.00002088625],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001304843,0.0002116556,0.9979522,0.0000672808,0.000014828,0.00001307348,0.00002551111,0.00007613044,0.0003345749],"genre_scores_gemma":[0.226391,0.001503222,0.765075,0.0005049768,0.0002456645,0.0004139975,0.0006349417,0.0002006641,0.005030554],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004033204,"threshold_uncertainty_score":0.0182637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2038141274851704,"score_gpt":0.5436401536883851,"score_spread":0.3398260262032148,"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."}}