{"id":"W7097008869","doi":"","title":"Author manuscript, published in "9th International IEEE Conference on Intelligent Transportation Systems (ITSC'2006), Toronto: Canada (2006)" Audio Events Detection in Public Transport Vehicle","year":2012,"lang":"en","type":"article","venue":"","topic":"Music and Audio Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Public transport; Intelligent transportation system; Control (management); Index (typography); Key (lock); Audio analyzer","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001238568,0.0004353377,0.0004598805,0.0003471689,0.0001623705,0.0003750887,0.001133077,0.0002291727,0.0004884599],"category_scores_gemma":[0.00007103123,0.0004190541,0.00009755971,0.000731863,0.00004123567,0.003796106,0.00003177884,0.000470263,0.00004185228],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001561786,"about_ca_system_score_gemma":0.0007265611,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3323426,"about_ca_topic_score_gemma":0.9421299,"domain_scores_codex":[0.9956543,0.0001731833,0.001160389,0.0008405413,0.001206245,0.0009653644],"domain_scores_gemma":[0.9982455,0.00007046842,0.000363886,0.0006094859,0.0003163124,0.0003943526],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007443216,0.00559294,0.4731665,0.001394682,0.0005496139,0.0001222786,0.04829396,0.01210623,0.01841685,0.06718998,0.07687962,0.295543],"study_design_scores_gemma":[0.003796586,0.0001891385,0.3951014,0.001067168,0.00005839273,0.00006989724,0.001784855,0.0265653,0.006676454,0.0009852437,0.5606697,0.003035974],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5097852,0.0002501788,0.4715874,0.003236359,0.009838945,0.0006733388,0.00005016564,0.000218194,0.004360211],"genre_scores_gemma":[0.9876074,0.00002649852,0.001856642,0.000598366,0.0002476553,0.0001221867,0.0001548396,0.00003051561,0.009355953],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6097873,"threshold_uncertainty_score":0.9998261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1085034734831457,"score_gpt":0.3032681950804142,"score_spread":0.1947647215972685,"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."}}