{"id":"W2087870069","doi":"10.1016/j.jspi.2014.01.005","title":"New optimal design criteria for regression models with asymmetric errors","year":2014,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Statistics; Regression; Regression analysis; Econometrics; Applied mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003949828,0.0001634228,0.00046344,0.0003147057,0.0001253189,0.0003194616,0.000334789,0.00007266513,0.00006181084],"category_scores_gemma":[0.008155651,0.00009261876,0.00004162717,0.0003109367,0.0001094548,0.0005906408,0.00004931992,0.0002181054,0.000003618655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002156031,"about_ca_system_score_gemma":0.0001395269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006301077,"about_ca_topic_score_gemma":8.168958e-8,"domain_scores_codex":[0.9975662,0.0003938534,0.0007044003,0.0002567519,0.00083925,0.0002395162],"domain_scores_gemma":[0.9888809,0.009731909,0.0004675888,0.000150816,0.0003948542,0.0003739471],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.007475519,0.0001992089,0.003148452,0.00004925625,0.0000990331,0.0001308352,0.002957353,0.09402903,0.00758198,0.1143414,0.06614708,0.7038408],"study_design_scores_gemma":[0.001738309,0.006049227,0.003988934,0.0003470619,0.0000537425,0.0002029067,0.0005951745,0.7820947,0.002303467,0.2012655,0.001040669,0.0003203636],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004185024,0.0002388394,0.9943968,0.0001105852,0.0001565756,0.00009773414,0.00001027904,0.000007791012,0.0007963623],"genre_scores_gemma":[0.4091864,0.000004017319,0.5906046,0.00005301863,0.00005892122,0.000001179413,5.403183e-7,0.000006757833,0.00008457067],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7035205,"threshold_uncertainty_score":0.9763666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2532434680156384,"score_gpt":0.491720987300366,"score_spread":0.2384775192847276,"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."}}