{"id":"W2792771708","doi":"10.1016/j.neuroimage.2018.03.044","title":"Auditory prediction cues motor preparation in the absence of movements","year":2018,"lang":"en","type":"article","venue":"NeuroImage","topic":"Action Observation and Synchronization","field":"Psychology","cited_by":50,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Concordia University; International Laboratory for Brain, Music and Sound Research","funders":"Natural Sciences and Engineering Research Council of Canada; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Transcranial magnetic stimulation; Psychology; Perception; Anticipation (artificial intelligence); Sensory system; Melody; Computer science; Speech recognition; Neuroscience; Cognitive psychology; Artificial intelligence; Stimulation","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":[0.0002970367,0.0003598848,0.0002492095,0.0002785526,0.0001567647,0.0004385202,0.0002316451,0.0006172815,0.003428712],"category_scores_gemma":[0.005084961,0.0002715818,0.00008721294,0.0001621492,0.0004520434,0.0003967662,0.0006065681,0.0007355508,0.0003048411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001707671,"about_ca_system_score_gemma":0.0004252428,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001589547,"about_ca_topic_score_gemma":0.002702937,"domain_scores_codex":[0.9998336,0.00002668755,0.000013901,0.00003507831,0.00005126411,0.00003945631],"domain_scores_gemma":[0.9991013,0.0005603351,0.0001432435,0.00005271459,0.00004108397,0.0001013363],"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":[0.01356529,0.0002000125,0.006190548,0.0001480711,0.00003207571,0.0008160546,0.000352303,0.0007434345,0.9458519,0.001155927,0.0007078128,0.0302367],"study_design_scores_gemma":[0.0007805846,0.003598406,0.7639455,0.0001642202,0.0001868416,0.002731776,0.0005131756,0.01895269,0.1949884,0.01026292,0.003800507,0.00007494201],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.991769,0.0003631616,0.002915923,0.0002600119,0.0001288524,0.00003398875,0.0001820084,0.00007460534,0.004272531],"genre_scores_gemma":[0.9979926,0.0001457994,0.0006111524,0.00006352962,0.00004497026,0.00001261597,0.0001098814,0.0000396225,0.000979699],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003428712,"threshold_uncertainty_score":0.01147026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03757050915056197,"score_gpt":0.3333342450993216,"score_spread":0.2957637359487597,"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."}}