{"id":"W259993126","doi":"","title":"Tire-Pavement Noise Measurement: Case Study from Ontario, Canada","year":2012,"lang":"en","type":"other","venue":"USC Research Bank (University of the Sunshine Coast)","topic":"Hermeneutics and Narrative Identity","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Noise (video); Environmental science; Computer science; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008479304,0.0005369643,0.0005140952,0.001701438,0.009342195,0.002206865,0.001644244,0.001286568,0.003239573],"category_scores_gemma":[0.002427356,0.0004042292,0.0003840163,0.005296707,0.002009453,0.0005509894,0.001373746,0.0008240584,0.0004064754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04793764,"about_ca_system_score_gemma":0.06834204,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9958823,"about_ca_topic_score_gemma":0.9990945,"domain_scores_codex":[0.9978289,0.0001395427,0.00007256368,0.0002048415,0.001237241,0.0005169275],"domain_scores_gemma":[0.9975636,0.0003197306,0.0001696735,0.0001032534,0.00160875,0.0002349486],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006654927,0.0007478805,0.5276181,0.001542112,0.0002143852,0.02495291,0.1710248,0.00752283,0.01833006,0.006934141,0.03368599,0.2067613],"study_design_scores_gemma":[0.00003623449,0.0002086275,0.6754811,0.0003659386,0.0001326987,0.001448415,0.2241566,0.004143715,0.005012573,0.0005339162,0.08833207,0.0001480285],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9490595,0.001026167,0.002216656,0.00098623,0.00003543549,0.0003592386,0.001485551,0.00006451298,0.04476669],"genre_scores_gemma":[0.9603376,0.001129402,0.003158449,0.0002361357,0.00001006913,0.00005928543,0.0005398634,0.0000469759,0.03448213],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04793764,"threshold_uncertainty_score":0.3478136,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1154100619565953,"score_gpt":0.2586101404238369,"score_spread":0.1432000784672416,"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."}}