{"id":"W4383742371","doi":"10.1016/j.jspi.2023.06.005","title":"Optimal designs for comparing curves in regression models with asymmetric errors","year":2023,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Natural Science Foundation of Anhui Province; National Natural Science Foundation of China","keywords":"Mathematics; Optimal design; Equivalence (formal languages); Particle swarm optimization; Mathematical optimization; Applied mathematics; Optimality criterion; Regression; Statistics; Discrete mathematics","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":[0.1760871,0.003055938,0.006310046,0.003909836,0.001424425,0.0034163,0.004603142,0.006472155,0.007529458],"category_scores_gemma":[0.3746616,0.00417431,0.004648723,0.002249499,0.007331165,0.005541441,0.005224755,0.007225956,0.0009628651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003159512,"about_ca_system_score_gemma":0.006024413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008247494,"about_ca_topic_score_gemma":0.0006461439,"domain_scores_codex":[0.7269424,0.2459432,0.006155852,0.01069069,0.008011211,0.002256603],"domain_scores_gemma":[0.5626751,0.3890232,0.0117937,0.02554744,0.008638366,0.002322111],"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":[0.03115436,0.002426592,0.005515127,0.002861955,0.002291447,0.0002270803,0.001187076,0.1688783,0.008127276,0.4008635,0.002476701,0.3739907],"study_design_scores_gemma":[0.01085195,0.008502146,0.003228897,0.0008290332,0.001384132,0.0001579393,0.0001989911,0.3732334,0.009921098,0.5856352,0.005772765,0.0002844049],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007899838,0.000205039,0.9897508,0.0001492247,0.00007106709,0.001162243,0.00008201416,0.0002311804,0.0004487057],"genre_scores_gemma":[0.1002607,0.0002093218,0.8874772,0.0002123869,0.00006250669,0.01101338,0.00017536,0.0001689479,0.0004200351],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1760871,"threshold_uncertainty_score":0.9312487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3955391675662318,"score_gpt":0.5122542929729154,"score_spread":0.1167151254066836,"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."}}