{"id":"W2095085804","doi":"10.1007/s00265-007-0461-8","title":"Food sharing among retaliators: sequential arrivals and information asymmetries","year":2007,"lang":"en","type":"article","venue":"Behavioral Ecology and Sociobiology","topic":"Evolutionary Game Theory and Cooperation","field":"Social Sciences","cited_by":34,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal; Université de Montréal","funders":"","keywords":"Animal ecology; Generality; Foraging; Dove; Resource (disambiguation); Biology; Ideal free distribution; Ecology; Competitor analysis; Evolutionarily stable strategy; Range (aeronautics); Game theory; Microeconomics; Computer science; Economics; Business; Marketing","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":[0.005855812,0.0003705768,0.0009995954,0.0007275753,0.0005928077,0.002393715,0.001005046,0.001689502,0.003843581],"category_scores_gemma":[0.03069397,0.0007182406,0.0004817198,0.0003811007,0.001103658,0.002963529,0.001387299,0.001212303,0.0003683441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005151326,"about_ca_system_score_gemma":0.0003957768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007342425,"about_ca_topic_score_gemma":0.001116891,"domain_scores_codex":[0.9986229,0.0006043368,0.00009179148,0.0002601906,0.0001925918,0.0002282448],"domain_scores_gemma":[0.9517704,0.03511797,0.006837669,0.003670469,0.00136447,0.001239022],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.006620412,0.001463286,0.458427,0.0008059119,0.001476445,0.003556683,0.008080288,0.0603332,0.09489766,0.1814473,0.002932556,0.1799594],"study_design_scores_gemma":[0.0003135934,0.0008790148,0.3925318,0.0001102915,0.0009963906,0.003665181,0.004216075,0.3568993,0.007125631,0.2312649,0.00174325,0.0002546821],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9888916,0.0001927009,0.007105827,0.0002533796,0.0000129475,0.00001701786,0.00004214665,0.00001372088,0.003470698],"genre_scores_gemma":[0.9985542,0.00005819733,0.0008774207,0.00003122541,0.00001400022,0.000008583917,0.0000155331,0.000004942519,0.0004359302],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005855812,"threshold_uncertainty_score":0.03096884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02661845652045651,"score_gpt":0.3196846121764474,"score_spread":0.2930661556559909,"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."}}