{"id":"W3205790946","doi":"10.2196/31724","title":"In Search of State and Trait Emotion Markers in Mobile-Sensed Language: Field Study","year":2021,"lang":"en","type":"article","venue":"JMIR Mental Health","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"KU Leuven; European Commission","keywords":"Trait; Psychology; Experience sampling method; Happiness; Valence (chemistry); Mood; Set (abstract data type); Cognitive psychology; Computer science; Social psychology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.007269021,0.0004670795,0.0003705407,0.0009869701,0.0005292095,0.001100951,0.0006534997,0.0006690781,0.001769005],"category_scores_gemma":[0.01337399,0.0002547248,0.0004625334,0.0006465843,0.0009234194,0.001030133,0.0007812268,0.0006464325,0.0006763119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004737703,"about_ca_system_score_gemma":0.0005280662,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004166779,"about_ca_topic_score_gemma":0.004575089,"domain_scores_codex":[0.9969012,0.001949451,0.0001607778,0.0005088481,0.0003219417,0.0001578137],"domain_scores_gemma":[0.9862626,0.008315331,0.001720609,0.000932787,0.00216753,0.0006011361],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001603953,0.003207547,0.914006,0.0006541447,0.0002725687,0.0002333867,0.009795818,0.0005073565,0.004988475,0.0003933622,0.001118713,0.06321863],"study_design_scores_gemma":[0.0001162103,0.005582437,0.97097,0.0002835943,0.000197913,0.0004788051,0.01379169,0.003679663,0.002032391,0.0004365957,0.002376296,0.0000544458],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970934,0.0002919557,0.00136469,0.000105814,0.00001579714,0.0001997347,0.0002058581,0.00000734171,0.0007153183],"genre_scores_gemma":[0.9961868,0.000204466,0.002305087,0.0001156672,0.00003418668,0.000291669,0.0002425435,0.000004590716,0.0006150054],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007269021,"threshold_uncertainty_score":0.03844273,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02753499368811125,"score_gpt":0.4058273722336037,"score_spread":0.3782923785454924,"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."}}