{"id":"W627114345","doi":"","title":"Case Studies to Determine the Relationship between Rehabilitation Process, Hot-Mix Asphalt Lift Thickness, and Pavement Smoothness","year":2011,"lang":"en","type":"article","venue":"","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Smoothness; Asphalt; Lift (data mining); Asphalt pavement; Engineering; Forensic engineering; Computer science; Mathematics; Cartography; Geography","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":[0.003476159,0.0006416891,0.000419825,0.001751616,0.001270359,0.0008928984,0.001106156,0.001383776,0.002340871],"category_scores_gemma":[0.006540746,0.0003722505,0.0008887757,0.001817602,0.0007176484,0.0007734103,0.000707499,0.0007385602,0.0002914359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002415853,"about_ca_system_score_gemma":0.001720853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03231779,"about_ca_topic_score_gemma":0.07942728,"domain_scores_codex":[0.9971306,0.001141223,0.0002901481,0.0002740168,0.0008385584,0.0003254408],"domain_scores_gemma":[0.9900723,0.00602041,0.001136805,0.0005331214,0.001805369,0.0004320594],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002334438,0.01662835,0.6955965,0.002615571,0.0006755547,0.06038951,0.01540652,0.07089438,0.02641652,0.009310958,0.005001514,0.0947303],"study_design_scores_gemma":[0.0007359207,0.02643697,0.6325942,0.0009895371,0.001171929,0.02904837,0.08684637,0.09851271,0.07018465,0.005334079,0.04762233,0.0005228995],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9887336,0.0003482981,0.005291471,0.000131195,0.00001492881,0.0007613729,0.0003956775,0.00002229708,0.004301064],"genre_scores_gemma":[0.9816383,0.0007635501,0.01393936,0.00005384003,0.00001191451,0.0004388684,0.0002594137,0.000009608075,0.002885101],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03231779,"threshold_uncertainty_score":0.06425935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05537541866366257,"score_gpt":0.2866131085801694,"score_spread":0.2312376899165068,"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."}}