{"id":"W2950377945","doi":"10.1371/journal.pone.0199847","title":"Spatiotemporal dynamics of reward and punishment effects induced by associative learning","year":2018,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Neural and Behavioral Psychology Studies","field":"Neuroscience","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Incentive salience; Associative learning; Punishment (psychology); Psychology; Salience (neuroscience); Cognitive psychology; Reinforcement learning; Association (psychology); Task (project management); Perception; Event-related potential; Incentive; Electroencephalography; Developmental psychology; Neuroscience; Addiction; Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001250576,0.0001545333,0.0001656353,0.0001639853,0.00009271517,0.0001874171,0.0001446614,0.0001848447,0.001757323],"category_scores_gemma":[0.001200395,0.000110613,0.0001046348,0.0001413039,0.0001875095,0.0002573149,0.000262658,0.0003062457,0.0001819279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001524281,"about_ca_system_score_gemma":0.0001007638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003885873,"about_ca_topic_score_gemma":0.0004788729,"domain_scores_codex":[0.9999442,0.000009029334,0.000002989651,0.00001314477,0.00001666532,0.00001396192],"domain_scores_gemma":[0.999689,0.0001174814,0.00007656485,0.00002275617,0.0000473122,0.00004695995],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007228034,0.00007997605,0.006552975,0.00006577095,0.00002479907,0.0003789426,0.0001362435,0.001584306,0.9741459,0.0007785693,0.0002471799,0.01528247],"study_design_scores_gemma":[0.0001318347,0.0009224528,0.7122812,0.00002746007,0.00006711636,0.00175272,0.0002109097,0.06527054,0.2105307,0.006941358,0.001813469,0.00005018947],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938851,0.0001180632,0.003881588,0.00004592441,0.000008590122,0.00001199025,0.00008692445,0.00006173997,0.001900125],"genre_scores_gemma":[0.9988081,0.00004893821,0.0007916283,0.00001013418,0.000004838465,0.000008490004,0.00005642802,0.00001218052,0.000259073],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001757323,"threshold_uncertainty_score":0.005878806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1313749693142366,"score_gpt":0.3279565477975867,"score_spread":0.1965815784833501,"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."}}