{"id":"W3001638326","doi":"10.1016/j.biopsycho.2020.107849","title":"Electroencephalographic evidence for a reinforcement learning advantage during motor skill acquisition","year":2020,"lang":"en","type":"article","venue":"Biological Psychology","topic":"Neural and Behavioral Psychology Studies","field":"Neuroscience","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University; University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Dreyfus model of skill acquisition; Task (project management); Negativity effect; Reinforcement learning; Reinforcement; Psychology; Electroencephalography; Motor learning; Motor skill; Qualitative property; Negative feedback; Cognitive psychology; Computer science; Neuroscience; Artificial intelligence; Machine learning; Social psychology; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001301534,0.000241048,0.0003115451,0.00006777707,0.0003325313,0.00001788111,0.0003716178,0.0001773565,0.0001688863],"category_scores_gemma":[0.00074432,0.0001736584,0.0001850829,0.0003189362,0.0003728725,0.0001375167,0.0001099747,0.0003485195,0.0001101368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001764542,"about_ca_system_score_gemma":0.000004814702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.277758e-7,"about_ca_topic_score_gemma":2.279626e-7,"domain_scores_codex":[0.9977147,0.0002260816,0.0003511031,0.0009868878,0.0001180866,0.0006031269],"domain_scores_gemma":[0.999172,0.0003262873,0.0001505785,0.0001665548,0.00003681622,0.0001477974],"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":[0.001237833,0.00006755243,0.01145285,0.00001220018,0.000005309489,0.00003879813,0.00006465297,0.00001070456,0.9858314,0.0001866782,0.0002938021,0.000798159],"study_design_scores_gemma":[0.006788963,0.03287511,0.5084373,0.0001134539,0.0001005674,0.0003566135,0.0002595799,0.0002613481,0.4300699,0.003722851,0.01525097,0.0017634],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9900733,0.0002587233,0.001271259,0.006812472,0.0003210124,0.0006516151,0.000006563194,0.0002790154,0.0003261039],"genre_scores_gemma":[0.9858652,0.0008388082,0.0001439605,0.01252755,0.0002642797,0.0002057361,0.000005484832,0.00001251474,0.000136453],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5557616,"threshold_uncertainty_score":0.7081586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3166602236147564,"score_gpt":0.443255616916465,"score_spread":0.1265953933017086,"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."}}