{"id":"W3165295356","doi":"10.48550/arxiv.2105.12364","title":"Basic and Depression Specific Emotion Identification in Tweets: Multi-label Classification Experiments","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Text and Document Classification Technologies","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Identification (biology); Depression (economics); Multi-label classification; Psychology; Emotion classification; Computer science; Cognitive psychology; Artificial intelligence; Biology; Economics","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":[0.005846021,0.001313274,0.001198583,0.001172049,0.001152352,0.001087697,0.001097232,0.002455772,0.001894484],"category_scores_gemma":[0.01229792,0.0002667709,0.0009759752,0.0009543311,0.0008185547,0.001886507,0.001579012,0.002459928,0.00145911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006363801,"about_ca_system_score_gemma":0.0005310078,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002192042,"about_ca_topic_score_gemma":0.00292443,"domain_scores_codex":[0.996506,0.001550038,0.0003331845,0.0006578591,0.0006204903,0.000332437],"domain_scores_gemma":[0.9879736,0.008380864,0.0006807109,0.001110179,0.001153997,0.0007006301],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0272019,0.03118937,0.2680006,0.00275461,0.001843164,0.001997085,0.00383668,0.06763826,0.05853602,0.002307499,0.05227505,0.4824199],"study_design_scores_gemma":[0.001238327,0.007455713,0.2097412,0.0002503895,0.0006713998,0.001471076,0.004560534,0.707087,0.04923945,0.006933954,0.01106707,0.0002837379],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.983462,0.0008437966,0.008950314,0.0006360172,0.0003480728,0.0003986034,0.002558885,0.0004729692,0.002329246],"genre_scores_gemma":[0.9680279,0.0002223229,0.02101306,0.0003574682,0.0002174366,0.0003714416,0.007503574,0.00008411855,0.002202605],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005846021,"threshold_uncertainty_score":0.03091711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1548741197765774,"score_gpt":0.2415060054374536,"score_spread":0.08663188566087623,"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."}}