{"id":"W2278272317","doi":"","title":"Motor Performance in the Context of Externally-imposed Payoffs","year":2013,"lang":"en","type":"dissertation","venue":"TSpace (University of Toronto)","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto","keywords":"Context (archaeology); Psychology; Value (mathematics); Selection (genetic algorithm); Process (computing); Cognitive psychology; Social psychology; Computer science; Artificial intelligence; Machine learning","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006829802,0.0003124502,0.0002514451,0.0001352659,0.0002121201,0.001108047,0.0003211241,0.0003733851,0.00209518],"category_scores_gemma":[0.007650126,0.0001651772,0.0001179159,0.0001303019,0.0006375806,0.000479867,0.0009800466,0.0004277841,0.0003007984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003397556,"about_ca_system_score_gemma":0.0003392033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001873019,"about_ca_topic_score_gemma":0.002003792,"domain_scores_codex":[0.999391,0.0002202577,0.00003470893,0.0001447599,0.0001429723,0.00006636066],"domain_scores_gemma":[0.9989458,0.0005535476,0.0002589995,0.00009223277,0.0000667996,0.00008269585],"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":[0.002449736,0.0003645254,0.02601206,0.000514842,0.0001120768,0.0007474088,0.007851051,0.01682799,0.8796158,0.005593458,0.0006858141,0.05922511],"study_design_scores_gemma":[0.0003588934,0.005550698,0.6775943,0.0002726305,0.0001749558,0.001038921,0.005258441,0.1059381,0.1716592,0.02439956,0.0075124,0.0002420697],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950383,0.00004935205,0.001659536,0.00003231722,0.000005135651,0.00002160069,0.00003144132,0.00001731937,0.00314486],"genre_scores_gemma":[0.997548,0.00007093879,0.001518886,0.00001138341,0.000001987902,0.00002316657,0.00004492258,0.00001026003,0.0007704069],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00209518,"threshold_uncertainty_score":0.007009089,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01786152430246021,"score_gpt":0.2304072827765044,"score_spread":0.2125457584740442,"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."}}