{"id":"W2058971217","doi":"10.1111/j.1558-5646.2008.00449.x","title":"ESTIMATING NONLINEAR SELECTION GRADIENTS USING QUADRATIC REGRESSION COEFFICIENTS: DOUBLE OR NOTHING?","year":2008,"lang":"en","type":"article","venue":"Evolution","topic":"Animal Behavior and Reproduction","field":"Agricultural and Biological Sciences","cited_by":507,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Nonlinear regression; Regression; Selection (genetic algorithm); Quadratic equation; Statistics; Regression analysis; Linear regression; Mathematics; Polynomial regression; Directional selection; Applied mathematics; Biology; Natural selection; Computer science; Artificial intelligence","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":[0.02064014,0.001403709,0.001371824,0.002871568,0.000562936,0.002059628,0.00110317,0.0009116851,0.002311422],"category_scores_gemma":[0.08291852,0.0005890499,0.00105883,0.00411121,0.001134514,0.003751853,0.001124833,0.001645861,0.001492611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004930642,"about_ca_system_score_gemma":0.0006733808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002754468,"about_ca_topic_score_gemma":0.004973085,"domain_scores_codex":[0.9904338,0.005032661,0.0009052196,0.001379888,0.001858762,0.000389677],"domain_scores_gemma":[0.9414601,0.03666256,0.005488456,0.008272846,0.007284793,0.000831336],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005368249,0.0001513697,0.2244769,0.001368738,0.001904696,0.0004329557,0.001050534,0.007987321,0.02006118,0.0123421,0.0133896,0.7162979],"study_design_scores_gemma":[0.0003107753,0.001234358,0.5019594,0.001572246,0.002300486,0.005657664,0.002181977,0.1481929,0.05811549,0.1422128,0.1349691,0.001292687],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2255863,0.01173956,0.7431679,0.004157776,0.001468551,0.0002425127,0.001342379,0.002391058,0.009903964],"genre_scores_gemma":[0.7232518,0.003446412,0.2636071,0.001276361,0.0005773398,0.0002279489,0.001144399,0.001304993,0.005163634],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02064014,"threshold_uncertainty_score":0.1091568,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05899087293662813,"score_gpt":0.2879706462540791,"score_spread":0.228979773317451,"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."}}