{"id":"W2612919868","doi":"10.21437/interspeech.2017-43","title":"The INTERSPEECH 2017 Computational Paralinguistics Challenge: Addressee, Cold & Snoring","year":2017,"lang":"en","type":"article","venue":"","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":131,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Engineering and Physical Sciences Research Council; Social Sciences and Humanities Research Council of Canada; National Institutes of Health; National Science Foundation","keywords":"Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0003973565,0.0001289374,0.0001108941,0.00003718731,0.00129373,0.001451246,0.00303485,0.00006189606,0.00000618028],"category_scores_gemma":[0.0006221092,0.00008705303,0.0000463964,0.00004458499,0.0001455817,0.0003591855,0.0008883247,0.0002284264,0.0000527108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003798758,"about_ca_system_score_gemma":0.00005510763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005178105,"about_ca_topic_score_gemma":0.0001186916,"domain_scores_codex":[0.9989326,0.00002807995,0.0001815372,0.0002909313,0.0003087116,0.0002581207],"domain_scores_gemma":[0.9981092,0.0002143825,0.0002087953,0.001125949,0.0002771804,0.00006454022],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000004135942,0.00002487977,0.0000966732,0.00001295028,0.0000198472,0.0000260924,0.0003121387,0.00002380376,0.0000968292,0.964619,0.01481929,0.01994436],"study_design_scores_gemma":[0.0005439566,0.00008898159,0.0007517748,0.0002125497,0.00001889343,0.00006858201,0.00003761838,0.05016771,0.006880864,0.7609525,0.1794688,0.0008077328],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002821056,0.001940092,0.9713501,0.006848317,0.0008039934,0.0001629734,0.000002283634,0.0006559631,0.0179542],"genre_scores_gemma":[0.4822585,0.00003606384,0.5153117,0.0001465659,0.0001405225,0.0000106293,0.000001412341,0.000007061504,0.002087546],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4819764,"threshold_uncertainty_score":0.9995853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05487383178131913,"score_gpt":0.3532667099149649,"score_spread":0.2983928781336458,"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."}}