{"id":"W2509098370","doi":"","title":"A data processing method for noise measurements of snowmobiles and their sub-systems on test bench","year":2016,"lang":"en","type":"article","venue":"Canadian acoustics","topic":"Winter Sports Injuries and Performance","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Test bench; Noise (video); Noise reduction; Data processing; Computer science; Test data; Algorithm; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0003284399,0.0001074722,0.0002106748,0.00009246876,0.00006374424,0.00001580636,0.0001325081,0.00005907225,0.00001022552],"category_scores_gemma":[0.0002801361,0.00006569363,0.00001695023,0.00005877455,0.00005533093,0.0000630711,0.00002095941,0.00004820504,0.000001031564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008117386,"about_ca_system_score_gemma":0.0004694775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001406087,"about_ca_topic_score_gemma":0.002707064,"domain_scores_codex":[0.9992787,0.000006347412,0.0002002781,0.0001975649,0.00009956381,0.000217581],"domain_scores_gemma":[0.9989982,0.0001040524,0.00008334823,0.0003944114,0.0001756219,0.0002443525],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002474988,0.0001618063,0.09472066,0.002713849,0.0001821162,0.00002514184,0.0009598354,0.00005018276,0.2807138,0.00007687884,0.08832068,0.5318275],"study_design_scores_gemma":[0.01149286,0.005805592,0.3226886,0.01534536,0.001539245,0.0004369522,0.002882998,0.1464851,0.06904693,0.0002750615,0.4218358,0.002165503],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8093669,0.004040093,0.1557745,0.004638175,0.00188349,0.00367998,0.01634989,0.0000909929,0.004176009],"genre_scores_gemma":[0.9963128,0.00004339849,0.002697929,0.000292367,0.0002246275,0.00001443738,0.00004777378,0.00002069949,0.0003459685],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.529662,"threshold_uncertainty_score":0.2678908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06938236104953625,"score_gpt":0.3132875684918983,"score_spread":0.243905207442362,"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."}}