{"id":"W2963223838","doi":"","title":"WASSA-2017 shared task on emotion intensity","year":2019,"lang":"en","type":"article","venue":"Research Commons (University of Waikato)","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":264,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Sadness; Computer science; Task (project management); Anger; Emotion classification; Artificial intelligence; Natural language processing; Psychology; Social psychology","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":[0.00806587,0.00444607,0.002859193,0.00351952,0.002894063,0.003927169,0.002971551,0.00321731,0.01523989],"category_scores_gemma":[0.02007667,0.000792961,0.002471271,0.002677865,0.00124316,0.005179639,0.008976122,0.004054253,0.02124421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002749275,"about_ca_system_score_gemma":0.003280031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009749731,"about_ca_topic_score_gemma":0.01392413,"domain_scores_codex":[0.989509,0.003093447,0.001201367,0.002280117,0.002710365,0.001205687],"domain_scores_gemma":[0.9838772,0.003893377,0.0007457546,0.004268094,0.004996216,0.002219355],"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":[0.002345748,0.001095751,0.007809568,0.001864765,0.0003626136,0.0004636546,0.001412308,0.00356844,0.02484287,0.002176755,0.8283376,0.1257199],"study_design_scores_gemma":[0.001441122,0.001959324,0.0475137,0.0006646079,0.0004486379,0.001200645,0.004381308,0.08970591,0.06503163,0.01690192,0.7701215,0.0006297081],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.2226848,0.004293451,0.1085182,0.007406153,0.01103472,0.005498421,0.4861834,0.08375158,0.07062936],"genre_scores_gemma":[0.1788389,0.0004714559,0.08698969,0.001310112,0.0011077,0.004299963,0.6988781,0.004957399,0.02314668],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01523989,"threshold_uncertainty_score":0.05098253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08052660557195573,"score_gpt":0.3063275320859715,"score_spread":0.2258009265140157,"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."}}