{"id":"W2106121520","doi":"10.1093/beheco/arn037","title":"Food unpredictability drives both generalism and social foraging: a game theoretical model","year":2008,"lang":"en","type":"article","venue":"Behavioral Ecology","topic":"Animal Behavior and Reproduction","field":"Agricultural and Biological Sciences","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Cégep Marie-Victorin; McGill University","funders":"","keywords":"Foraging; Predictability; Generalist and specialist species; Biology; Resource (disambiguation); Cognition; Context (archaeology); Construct (python library); Ecology; Cognitive psychology; Social psychology; Psychology; Computer science; Habitat","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001260574,0.00014699,0.0002252194,0.00001154737,0.0003796562,0.00001578982,0.0001184925,0.0002114354,0.0002330274],"category_scores_gemma":[0.000007794962,0.00006344735,0.00009432089,0.00008358755,0.0007945732,0.00009824779,0.0001017726,0.0001663357,0.000005865896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003077239,"about_ca_system_score_gemma":0.00001463549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004853927,"about_ca_topic_score_gemma":0.0001587891,"domain_scores_codex":[0.998836,0.00007893115,0.0002029968,0.0004409104,0.0001224976,0.0003186293],"domain_scores_gemma":[0.9997394,0.00002326557,0.00005402948,0.00005074574,0.00004661586,0.00008590513],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002282793,0.001257884,0.6500727,0.00000842008,0.00001434251,0.00003522936,0.002266813,0.00001467254,0.3008129,0.02517889,0.000597249,0.0195126],"study_design_scores_gemma":[0.0002193494,0.001238787,0.9934565,9.558087e-7,0.0000437348,0.0001075799,0.0002348198,0.0003543581,0.0006836687,0.003119395,0.0003284292,0.0002124672],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979703,0.00003214882,0.00001103546,0.001456786,0.0001158127,0.0001959291,0.00004172952,0.00009988534,0.00007637806],"genre_scores_gemma":[0.9993132,0.00001840146,0.0001413386,0.0001305475,0.0002356863,0.00003408765,0.00004063821,0.000001705237,0.00008434316],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3433838,"threshold_uncertainty_score":0.2927638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05149723557675649,"score_gpt":0.2637157528034719,"score_spread":0.2122185172267154,"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."}}