{"id":"W2978044372","doi":"10.1016/j.biopsycho.2019.107778","title":"Behavioural and neural limits in competitive decision making: The roles of outcome, opponency and observation","year":2019,"lang":"en","type":"article","venue":"Biological Psychology","topic":"Neural and Behavioral Psychology Studies","field":"Neuroscience","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University; University of Alberta","funders":"University of Sussex","keywords":"Psychology; Negativity effect; Valence (chemistry); Outcome (game theory); Cognitive psychology; Dynamism; Set (abstract data type); Reinforcement; Developmental psychology; Social psychology; Economics; Computer science; Microeconomics; Chemistry","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":[0.001969632,0.0002312726,0.0003451388,0.0004854223,0.0002396261,0.001859798,0.0009139429,0.0005986473,0.002999421],"category_scores_gemma":[0.01340821,0.0003066474,0.0001685031,0.000321953,0.002440157,0.002609018,0.001048988,0.001102746,0.0001703309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000575413,"about_ca_system_score_gemma":0.0006829629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001408572,"about_ca_topic_score_gemma":0.001029821,"domain_scores_codex":[0.999301,0.0001726854,0.00004025329,0.0001192997,0.0002836989,0.00008301339],"domain_scores_gemma":[0.9899029,0.006195084,0.001691395,0.001052751,0.0004386724,0.0007192714],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00788773,0.001280724,0.08931267,0.0007915823,0.0002497034,0.0007606383,0.004977755,0.01444975,0.3675088,0.2583908,0.00076842,0.2536213],"study_design_scores_gemma":[0.000225651,0.001800193,0.5343493,0.0002373114,0.0001381711,0.001097655,0.001339877,0.03453908,0.03995473,0.3822987,0.003860824,0.0001584752],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9805195,0.000921312,0.00746208,0.0004296478,0.00002214278,0.000008046888,0.00004642927,0.00001860588,0.0105723],"genre_scores_gemma":[0.9973509,0.0002737299,0.001665911,0.00003658395,0.00002029943,0.00001128737,0.00001985383,0.00001917846,0.0006022052],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002999421,"threshold_uncertainty_score":0.01041657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3836823282147035,"score_gpt":0.4419716232379692,"score_spread":0.05828929502326569,"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."}}