{"id":"W4387814951","doi":"10.1145/3606039","title":"Proceedings of the 4th on Multimodal Sentiment Analysis Challenge and Workshop: Mimicked Emotions, Humour and Personalisation","year":2023,"lang":"en","type":"paratext","venue":"","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sentiment analysis; Disappointment; Personalization; Valence (chemistry); Computer science; Multimedia; Psychology; World Wide Web; Artificial intelligence; Social psychology; Chemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003793901,0.0002696351,0.0004859266,0.0005967499,0.0002216071,0.0002682426,0.0004424155,0.0001627596,0.0002116226],"category_scores_gemma":[0.00001981207,0.00018837,0.0002804396,0.001270144,0.00007513873,0.0001722865,0.0003884943,0.0002051147,0.00008184202],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003811329,"about_ca_system_score_gemma":0.00002627,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007804014,"about_ca_topic_score_gemma":0.00002650768,"domain_scores_codex":[0.9981187,0.00004024638,0.000392981,0.000698439,0.000536961,0.0002126559],"domain_scores_gemma":[0.9990046,0.0001127594,0.0003955364,0.0002743981,0.0001401431,0.00007253498],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008224321,0.001326607,0.01302081,0.001156677,0.01940826,0.000005739693,0.0542881,0.003646259,0.001620269,0.05944344,0.8082315,0.03777007],"study_design_scores_gemma":[0.001818634,0.0002591887,0.05849659,0.001031002,0.003182866,0.000005564391,0.009687876,0.9101205,0.001404585,0.0003440716,0.01195858,0.00169058],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8327231,0.004100241,0.02144691,0.0341032,0.004249541,0.002945012,0.0001296371,0.0004275365,0.09987482],"genre_scores_gemma":[0.7435031,0.001935815,0.004892045,0.0002863549,0.0003200632,0.00004651412,0.0001053512,0.00004476288,0.248866],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9064742,"threshold_uncertainty_score":0.7681504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03358999919223172,"score_gpt":0.2804198471977805,"score_spread":0.2468298480055487,"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."}}