{"id":"W4235838546","doi":"10.31234/osf.io/m5ge3","title":"Simulating Semantics: Are Individual Differences in Motor Imagery Related to Sensorimotor Effects in Language Processing?","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Action Observation and Synchronization","field":"Psychology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Motor imagery; Embodied cognition; Cognitive psychology; Task (project management); Psychology; Sentence; Semantics (computer science); Sentence processing; Mechanism (biology); Natural language processing; Computer science; Artificial intelligence; Brain–computer interface; Electroencephalography; Neuroscience","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003722828,0.0003156068,0.0005604689,0.0005487435,0.00005057296,0.0001918105,0.0002215595,0.0006017824,0.0009038245],"category_scores_gemma":[0.0005897455,0.0003134772,0.00007461408,0.0006083859,0.00002638991,0.0001258968,0.0002725625,0.0008562952,0.00007228782],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001617921,"about_ca_system_score_gemma":0.000106317,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004048353,"about_ca_topic_score_gemma":0.000382286,"domain_scores_codex":[0.9974618,0.000446793,0.0007056336,0.0007436904,0.0003099215,0.0003321408],"domain_scores_gemma":[0.9987691,0.0002933689,0.000351849,0.0003703589,0.0001295238,0.00008581533],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004000885,0.0003643192,0.9503867,0.0006801562,0.00006587133,0.0003518619,0.03186432,0.001765221,0.0003990508,0.0000667998,0.000167077,0.0138486],"study_design_scores_gemma":[0.0007738754,0.00003221671,0.9670885,0.0009204147,0.000019382,0.000003921571,0.009940646,0.0206726,0.00008694908,0.00005875415,0.00001633269,0.0003863864],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992507,0.0003152675,0.002758994,0.0004250075,0.001092458,0.00093795,0.00001423007,0.0001759097,0.001773147],"genre_scores_gemma":[0.9938084,0.000003839547,0.001804208,0.0005723063,0.0001050448,0.0001384449,0.0001915858,0.00004565986,0.003330548],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02192367,"threshold_uncertainty_score":0.9999318,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03157758217578781,"score_gpt":0.3288709416227851,"score_spread":0.2972933594469973,"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."}}