{"id":"W633951690","doi":"","title":"Saguenay Wayside Horn Evaluation Project","year":2006,"lang":"en","type":"article","venue":"","topic":"Smart Materials for Construction","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"French horn; Reliability (semiconductor); Environmental science; Snow; Engineering; Sound (geography); Aeronautics; Forensic engineering; Meteorology; Transport engineering; Geography; Geology; Acoustics; Oceanography","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":[0.0009058366,0.0004076066,0.0002477187,0.0006103861,0.001473375,0.001008572,0.0006468496,0.0003409258,0.007088098],"category_scores_gemma":[0.001356938,0.0001903859,0.0002177389,0.0006516016,0.0004526404,0.0003925807,0.0006885493,0.0004076881,0.0007197195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01028882,"about_ca_system_score_gemma":0.01133441,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8918644,"about_ca_topic_score_gemma":0.9639099,"domain_scores_codex":[0.9990082,0.0001783198,0.00001983806,0.00009660765,0.0005290577,0.0001679721],"domain_scores_gemma":[0.9968041,0.0001270996,0.0001177632,0.00009390273,0.00250111,0.0003559999],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002490482,0.001304859,0.4198607,0.0004619023,0.0002730247,0.00184542,0.007567741,0.01331003,0.06905037,0.002493332,0.03373871,0.4476034],"study_design_scores_gemma":[0.0002080749,0.002693436,0.8255878,0.0001421825,0.0001566285,0.0004250626,0.01031775,0.01098765,0.01756211,0.000267162,0.1315196,0.0001326576],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9398072,0.0004759447,0.004899368,0.0004737369,0.000047285,0.0007326764,0.003526193,0.0005639235,0.04947363],"genre_scores_gemma":[0.9310283,0.0003905901,0.0086873,0.0002142794,0.000009593731,0.0002126335,0.003648919,0.0001227666,0.05568561],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1081356,"threshold_uncertainty_score":0.2175448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01546728979851737,"score_gpt":0.2425616123037138,"score_spread":0.2270943225051965,"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."}}