{"id":"W2153704483","doi":"10.1177/0956797610387441","title":"Better Mood and Better Performance","year":2010,"lang":"en","type":"article","venue":"Psychological Science","topic":"Neural and Behavioral Psychology Studies","field":"Neuroscience","cited_by":141,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Mood; Cognitive flexibility; Cognition; Flexibility (engineering); Cognitive psychology; Set (abstract data type); Prefrontal cortex; Anterior cingulate cortex; Selection (genetic algorithm); Negative mood; Developmental psychology; Clinical psychology; Neuroscience; 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":[0.0004211869,0.0004658658,0.0003841661,0.0003902545,0.0003519144,0.0009323645,0.000129777,0.0005277608,0.009195154],"category_scores_gemma":[0.001943586,0.0001227124,0.0002544486,0.000199864,0.0002532993,0.0001954634,0.0005018784,0.0006069387,0.001754979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002147405,"about_ca_system_score_gemma":0.0001217714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007246938,"about_ca_topic_score_gemma":0.0007537407,"domain_scores_codex":[0.999734,0.00005933131,0.00003209598,0.00006153615,0.00004788739,0.00006517029],"domain_scores_gemma":[0.9981773,0.0002315256,0.0005921038,0.0002044315,0.0002227133,0.0005719416],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00801347,0.006299494,0.598846,0.0007142515,0.0008318661,0.001414659,0.00186266,0.0008562194,0.216882,0.002103659,0.005807898,0.1563678],"study_design_scores_gemma":[0.0001239705,0.001913004,0.9887478,0.00003809113,0.0001137734,0.0004659078,0.000193971,0.0004832598,0.004303216,0.001317053,0.002269068,0.00003071785],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.98752,0.0005058026,0.0005545169,0.0003216207,0.0001326689,0.00003558514,0.0002673565,0.00006264314,0.01059979],"genre_scores_gemma":[0.9948507,0.0002103814,0.0006407755,0.000230302,0.00005716411,0.00002380581,0.0002300158,0.00001349559,0.003743389],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009195154,"threshold_uncertainty_score":0.03076082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1298095179542765,"score_gpt":0.4038474744447408,"score_spread":0.2740379564904644,"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."}}