{"id":"W2408373116","doi":"10.1093/beheco/arw072","title":"Selection for multicomponent mimicry: equal feature salience and variation in preferred traits","year":2016,"lang":"en","type":"article","venue":"Behavioral Ecology","topic":"Animal Behavior and Reproduction","field":"Agricultural and Biological Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Mimicry; Batesian mimicry; Predation; Biology; Categorization; Salience (neuroscience); Aposematism; Selection (genetic algorithm); Population; Crypsis; Evolutionary biology; Salient; Ecology; Predator; Cognitive psychology; Artificial intelligence; Psychology; Computer science; Demography","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":[0.001837797,0.0003126569,0.0005800712,0.0007467744,0.0003604237,0.0008450356,0.0003787724,0.0005289355,0.001669449],"category_scores_gemma":[0.003407242,0.0002380135,0.0003291314,0.0002582355,0.0009007471,0.0004790289,0.0009061379,0.0004848761,0.0001252212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003318365,"about_ca_system_score_gemma":0.0002873665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005982575,"about_ca_topic_score_gemma":0.001748244,"domain_scores_codex":[0.9991488,0.0003280885,0.00006202329,0.0002534278,0.0001316582,0.00007596455],"domain_scores_gemma":[0.9963018,0.001497689,0.0009333587,0.0005974652,0.0002348522,0.0004348163],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001283911,0.0002721744,0.5112922,0.0001387053,0.0005280787,0.0005347959,0.000695924,0.001839816,0.4620721,0.001578389,0.0001427261,0.01962111],"study_design_scores_gemma":[0.00003591795,0.0005775536,0.9757603,0.000008526649,0.0001312174,0.0006988659,0.0002880071,0.009789484,0.01106891,0.001389681,0.0002101284,0.00004145094],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988511,0.00003187928,0.0007536214,0.00002660207,0.00000203549,0.000004580691,0.000008573165,0.000005741792,0.000315841],"genre_scores_gemma":[0.9993612,0.000007763768,0.0005100541,0.00001987674,0.000002492556,0.00000372671,0.00001013547,0.000003631348,0.00008111648],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001837797,"threshold_uncertainty_score":0.009719253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0436689657399092,"score_gpt":0.2760078431094656,"score_spread":0.2323388773695564,"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."}}