{"id":"W2009027314","doi":"10.3389/fnhum.2012.00053","title":"Flexible recruitment of semantic richness: context modulates body-object interaction effects in lexical-semantic processing","year":2012,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Action Observation and Synchronization","field":"Psychology","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Object (grammar); Computer science; Context (archaeology); Natural language processing; Cognitive psychology; Semantic memory; Psychology; Artificial intelligence; Communication; Neuroscience; Biology; Cognition","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":[0.0004715798,0.0001597789,0.0002795201,0.0004994409,0.0001254657,0.00003886506,0.0002159492,0.00009270212,0.00004004363],"category_scores_gemma":[0.0001692618,0.0001601467,0.00004194694,0.0009161244,0.0001696187,0.0007220243,0.00004144085,0.0002245582,0.000005799735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001610088,"about_ca_system_score_gemma":0.00002645419,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006326914,"about_ca_topic_score_gemma":0.0000130798,"domain_scores_codex":[0.9982532,0.0002425906,0.0004881882,0.0003768907,0.0002453347,0.0003938141],"domain_scores_gemma":[0.999316,0.00005399529,0.0002682889,0.000246922,0.00004678592,0.00006805437],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006086148,0.0008160652,0.9533759,0.0002014112,0.000004991425,0.000009698091,0.004463634,0.001250383,0.02063399,0.002623734,0.0009876541,0.01557165],"study_design_scores_gemma":[0.00114947,0.0002144782,0.9448026,0.0002899713,0.0000160331,0.00001356948,0.001440129,0.03927113,0.01029018,0.0007677203,0.001448761,0.0002959729],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8695224,0.0003968076,0.1239148,0.0000935576,0.004180542,0.000750627,8.79752e-7,0.00006740003,0.001072956],"genre_scores_gemma":[0.998493,0.00001380854,0.0002855182,0.0002895632,0.0000564727,0.000103545,0.000004805991,0.00001861948,0.0007347235],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1289705,"threshold_uncertainty_score":0.6530594,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07784978131328105,"score_gpt":0.3623068466604595,"score_spread":0.2844570653471785,"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."}}