{"id":"W4389524382","doi":"10.18653/v1/2023.emnlp-main.188","title":"Language and Mental Health: Measures of Emotion Dynamics from Text as Linguistic Biosocial Markers","year":2023,"lang":"en","type":"article","venue":"","topic":"Mental Health Research Topics","field":"Psychology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Carleton University; University of Alberta","funders":"Social Sciences and Humanities Research Council of Canada; Alliance de recherche numérique du Canada; Alberta Innovates; Bayerische Akademie der Wissenschaften; Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research","keywords":"Biosocial theory; Valence (chemistry); Mental health; Psychology; Psychopathology; Clinical psychology; Dynamics (music); Emotional valence; Utterance; Psychological intervention; Cognitive psychology; Psychiatry; Social psychology; Computer science; Personality; Artificial intelligence; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001408718,0.0003104024,0.0002060357,0.002010767,0.000307656,0.001554744,0.0002292908,0.0004653357,0.002336078],"category_scores_gemma":[0.01471384,0.0001331139,0.0002467795,0.001659319,0.0003516006,0.001356128,0.0008535555,0.000573021,0.000488473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002901194,"about_ca_system_score_gemma":0.0001872821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001062035,"about_ca_topic_score_gemma":0.002188632,"domain_scores_codex":[0.9987984,0.0005927726,0.0001144021,0.0001889904,0.0002444183,0.00006097373],"domain_scores_gemma":[0.9911341,0.004531061,0.002929731,0.0003668276,0.0006873006,0.0003509744],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008647067,0.0003152629,0.8042337,0.001103269,0.0004441523,0.0002588972,0.0130661,0.0006959212,0.02568787,0.001366892,0.002279596,0.1496837],"study_design_scores_gemma":[0.000007080029,0.000154661,0.9911342,0.00008454068,0.00005254634,0.0003038226,0.002660158,0.001377806,0.001306069,0.001037758,0.001842046,0.00003931008],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9846306,0.00127236,0.00430152,0.0005634617,0.00005896556,0.00009707612,0.003002504,0.00005597504,0.006017574],"genre_scores_gemma":[0.991939,0.0005301762,0.005111326,0.0001445419,0.00007526106,0.000130739,0.001243673,0.0000196975,0.00080557],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002336078,"threshold_uncertainty_score":0.007815003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07002200574485941,"score_gpt":0.4379703725748955,"score_spread":0.3679483668300361,"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."}}