{"id":"W2911439292","doi":"10.1145/3257283","title":"Session details: PAPER SESSION 1: Acoustic Sensing","year":2017,"lang":"en","type":"article","venue":"","topic":"Music and Audio Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bell (Canada)","funders":"","keywords":"Session (web analytics); Computer science; Speech recognition; World Wide Web","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002170111,0.0001173305,0.0001240096,0.00003560655,0.001131543,0.0009178533,0.000699208,0.00006369422,0.00008048287],"category_scores_gemma":[0.00009935729,0.00008305973,0.00004077168,0.00005380174,0.000049896,0.001688241,0.0005189063,0.000114303,0.0001078643],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001915387,"about_ca_system_score_gemma":0.00006858671,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002737588,"about_ca_topic_score_gemma":0.00001338672,"domain_scores_codex":[0.999011,0.00002581026,0.0001431327,0.0003344795,0.0002314073,0.0002541724],"domain_scores_gemma":[0.9988124,0.00003944732,0.0001442714,0.0008480005,0.00006327336,0.00009263882],"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":[0.000002384842,0.00001959213,0.0004842274,0.00003044907,0.000004755504,0.00004578905,0.0002789362,0.00005893913,0.07715176,0.001347387,0.00569885,0.9148769],"study_design_scores_gemma":[0.001442102,0.00008500113,0.02867217,0.001217914,0.00003765636,0.0001931731,0.0002446099,0.8030741,0.09960651,0.01837563,0.04570132,0.001349828],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02681594,0.00004999015,0.9307417,0.002924255,0.0005890463,0.00004985785,1.145054e-7,0.0001956389,0.03863346],"genre_scores_gemma":[0.9258451,0.000008049209,0.06971416,0.001921807,0.0001398494,5.596618e-7,3.167027e-7,0.000007359441,0.002362821],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9135271,"threshold_uncertainty_score":0.885088,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02907858566164602,"score_gpt":0.2813720857497896,"score_spread":0.2522935000881436,"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."}}