{"id":"W2160234840","doi":"10.1017/s0140525x10000865","title":"The Simulation of Smiles (SIMS) model: Embodied simulation and the meaning of facial expression","year":2010,"lang":"en","type":"review","venue":"Behavioral and Brain Sciences","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":617,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; Centre National de la Recherche Scientifique; Agence Nationale de la Recherche; Fonds De La Recherche Scientifique - FNRS; Mind Science Foundation; European Commission; Klingenstein Third Generation Foundation; National Alliance for Research on Schizophrenia and Depression; James S. McDonnell Foundation; National Science Foundation","keywords":"Embodied cognition; Psychology; Facial expression; Cognitive psychology; Cognitive science; Cognition; Perception; Gaze; Meaning (existential); Mimicry; Expression (computer science); Communication; Neuroscience; Computer science; Artificial intelligence","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":[0.0005584182,0.001105909,0.001101358,0.001372219,0.0002066141,0.000786855,0.001567235,0.001470722,0.001858204],"category_scores_gemma":[0.0008973817,0.0002866668,0.000485392,0.001202712,0.00138501,0.001472391,0.000768843,0.001460775,0.001412331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000984526,"about_ca_system_score_gemma":0.0007732566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001917912,"about_ca_topic_score_gemma":0.001691548,"domain_scores_codex":[0.9998521,0.00004979861,0.00001639855,0.00002487575,0.00004846024,0.00000833909],"domain_scores_gemma":[0.9996939,0.0002026096,0.00002696936,0.00001422477,0.00004480117,0.0000175848],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00007578016,0.00005466695,0.0003066137,0.007579477,0.0001013926,0.0003059306,0.0002744004,0.006264484,0.002228444,0.07462633,0.01399121,0.8941912],"study_design_scores_gemma":[0.00003586213,0.0001464696,0.001733997,0.004227023,0.0001540351,0.003151702,0.00030286,0.009266217,0.002205919,0.07361685,0.9050742,0.00008491363],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0006095627,0.98892,0.00441118,0.0005125907,0.0002194377,0.00001019187,0.00001551376,0.00002661588,0.005274984],"genre_scores_gemma":[0.008827693,0.9852105,0.003535314,0.0001778509,0.0001909252,0.00002838272,0.00003753148,0.000009154589,0.00198269],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.001917912,"threshold_uncertainty_score":0.007143199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2451184222547912,"score_gpt":0.4359491566311617,"score_spread":0.1908307343763705,"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."}}