{"id":"W2951934610","doi":"10.48550/arxiv.1309.6352","title":"Using Nuances of Emotion to Identify Personality","year":2013,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Affect (linguistics); Admiration; Psychology; Personality; Big Five personality traits; Emotion recognition; Cognitive psychology; Social psychology; Communication","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009356608,0.000511607,0.0003690237,0.002077961,0.0003284533,0.001104579,0.0001634836,0.0003729149,0.001565417],"category_scores_gemma":[0.004729002,0.0001182277,0.0003305782,0.0008845255,0.0002338583,0.0009419036,0.0005113329,0.0005387893,0.0008957825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001836288,"about_ca_system_score_gemma":0.0001127532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008411799,"about_ca_topic_score_gemma":0.001387037,"domain_scores_codex":[0.9995154,0.0001525178,0.0000421452,0.0001198408,0.0001223669,0.00004772972],"domain_scores_gemma":[0.9967977,0.00152859,0.0006857511,0.000229332,0.0005662353,0.000192351],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005273474,0.00024193,0.5552893,0.000304642,0.0002582645,0.0002560852,0.001673797,0.002477905,0.05373229,0.001400879,0.004349388,0.3794883],"study_design_scores_gemma":[0.00001770491,0.0003550853,0.8780769,0.00009301948,0.0001396829,0.0007366117,0.001734999,0.09420485,0.01158276,0.006094929,0.006890887,0.00007267178],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.934681,0.00100765,0.05224396,0.0003308762,0.0001006611,0.00008597333,0.001187606,0.0003277912,0.01003446],"genre_scores_gemma":[0.986668,0.0002034587,0.01133274,0.00003788997,0.00005254164,0.00002648039,0.0005521391,0.00001601763,0.001110668],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002077961,"threshold_uncertainty_score":0.005236864,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.20456984687118,"score_gpt":0.2679143075536152,"score_spread":0.06334446068243521,"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."}}