{"id":"W4251187649","doi":"10.1037/e634112013-864","title":"Use of facial cues in the assessment of emotions in a Chinese and Quebec sample","year":2011,"lang":"en","type":"dataset","venue":"PsycEXTRA Dataset","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Sample (material); Psychology; Cognitive psychology; Chemistry; Chromatography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003162534,0.0001879922,0.0002975453,0.0003139242,0.00003658657,0.00004157885,0.0003637099,0.0001333713,0.0007120091],"category_scores_gemma":[0.0004862369,0.0001361681,0.00004071369,0.0003406224,0.0001980756,0.0002796775,0.00008803342,0.0003418906,0.0000167693],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001959352,"about_ca_system_score_gemma":0.00006801135,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03647657,"about_ca_topic_score_gemma":0.1549827,"domain_scores_codex":[0.9984313,0.0003995562,0.0003995533,0.0003414536,0.0002651066,0.0001630323],"domain_scores_gemma":[0.9986619,0.0005305302,0.0002065847,0.0005496563,0.00001456972,0.00003672411],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002384716,0.0004567484,0.001524738,0.0001362258,0.000002773457,0.000006229268,0.0001399661,0.000002397779,0.0009284433,0.00001936016,0.9958962,0.0008631274],"study_design_scores_gemma":[0.0004534701,0.00008105951,0.1317842,0.0001169969,0.00002433096,0.0000137783,0.00007045652,0.0000509502,0.0000319652,0.0001423282,0.867036,0.0001944168],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.03984268,0.000005495508,0.00001865208,0.00008742351,0.0001024073,0.0003534162,0.9595791,0.000003701833,0.000007140132],"genre_scores_gemma":[0.009053175,0.0006152157,0.0001824535,0.0002412259,0.00002136151,0.0000315641,0.9898462,0.00000594487,0.000002894888],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1302595,"threshold_uncertainty_score":0.9699396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1521514265219512,"score_gpt":0.3876616489913496,"score_spread":0.2355102224693985,"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."}}