{"id":"W3021091497","doi":"10.7554/elife.54687","title":"Efficient recognition of facial expressions does not require motor simulation","year":2020,"lang":"en","type":"article","venue":"eLife","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institut national de la recherche scientifique; Harvard University","keywords":"Facial expression; Facial expression recognition; Neuroscience; Computer science; Facial recognition system; Speech recognition; Biology; Communication; Artificial intelligence; Psychology; Pattern recognition (psychology)","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0000699711,0.00008204963,0.0001047082,0.00004855296,0.0001015557,0.00001706012,0.00007204622,0.00006241576,0.001074397],"category_scores_gemma":[0.0009991743,0.00006502243,0.00006541783,0.0001492692,0.0000494218,0.0001012269,0.00002980405,0.00008976716,0.0005420699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001348452,"about_ca_system_score_gemma":0.00001856798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003582117,"about_ca_topic_score_gemma":8.601878e-7,"domain_scores_codex":[0.9990044,0.0001008604,0.0002225942,0.0002379172,0.000317913,0.0001163678],"domain_scores_gemma":[0.9995161,0.0001373946,0.00009781837,0.00008311195,0.00006432005,0.0001012745],"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":[0.0000983227,0.0000468847,0.00002506066,0.00002054724,7.662636e-7,9.658747e-7,0.0008505764,0.004153283,0.9832994,0.00001021214,0.00007274474,0.01142127],"study_design_scores_gemma":[0.0004611492,0.0001048217,0.0008760923,0.00004188446,0.00000761408,6.371926e-7,0.0001866614,0.1186542,0.8757367,0.00003491365,0.003759549,0.0001357583],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950603,0.000002782343,0.002480211,0.0007126451,0.0002586455,0.0002291612,0.0002828326,0.0001038613,0.000869547],"genre_scores_gemma":[0.9977337,0.00001957761,0.0002036018,0.001725044,0.000178532,0.00001098209,0.00001671828,0.000009735431,0.0001020985],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.114501,"threshold_uncertainty_score":0.9998388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1270621013742384,"score_gpt":0.3263385970214964,"score_spread":0.1992764956472579,"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."}}