{"id":"W2599918346","doi":"","title":"Evidence against the automaticity of motor simulation in action prediction: Separately acquired visual-motor and visual representations can be used flexibly to aid in prediction accuracy","year":2016,"lang":"en","type":"article","venue":"","topic":"Action Observation and Synchronization","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Motor learning; Task (project management); Visual perception; Automaticity; Flexibility (engineering); Psychology; Computer science; Perception; Artificial intelligence; Engineering; Cognition; Mathematics; Statistics","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":[0.001246851,0.0004033733,0.0003447122,0.0003763588,0.0001854748,0.0006227199,0.0005913306,0.0005671624,0.002002276],"category_scores_gemma":[0.008186772,0.0003080023,0.0002486204,0.000109638,0.001310269,0.0007971183,0.00114414,0.001089558,0.0002155742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002777549,"about_ca_system_score_gemma":0.0003550011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001046485,"about_ca_topic_score_gemma":0.001187308,"domain_scores_codex":[0.9988754,0.0001903405,0.0001227635,0.0002756431,0.0003914068,0.0001444475],"domain_scores_gemma":[0.9916168,0.003022003,0.002020209,0.002270777,0.0004518236,0.0006184794],"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":[0.003896832,0.00154456,0.1243799,0.0003542278,0.0001768008,0.0003636846,0.001629601,0.00210617,0.7894439,0.001318768,0.0002990226,0.07448656],"study_design_scores_gemma":[0.0001533728,0.003992906,0.861336,0.00004957031,0.00008729447,0.0006842598,0.0003386915,0.01124706,0.1184116,0.002451569,0.001202352,0.00004517872],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962993,0.0000500728,0.00215561,0.00006702884,0.000007473405,0.00001405313,0.00003558069,0.0000286092,0.001342294],"genre_scores_gemma":[0.9976583,0.0000319963,0.001634356,0.00002445095,0.000003538499,0.00002808675,0.00006518536,0.00001242951,0.0005417698],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002002276,"threshold_uncertainty_score":0.006698251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1400364495338593,"score_gpt":0.4311873507301922,"score_spread":0.2911509011963329,"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."}}