{"id":"W2576495764","doi":"","title":"Use of Pavement Management System Data to Enhance Pavement Performance Specifications in Canada","year":2016,"lang":"en","type":"article","venue":"Transportation Research Board 95th Annual Meeting","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Golder Associates (Canada); Ministry of Transportation of Ontario","funders":"","keywords":"Bridge (graph theory); Transport engineering; Quality assurance; Pavement management; Christian ministry; Payment; Engineering; Agency (philosophy); Computer science; Operations management","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005774421,0.0001282446,0.0001640088,0.0002110061,0.00007101843,0.00001664945,0.0003777758,0.00002601746,0.00001427487],"category_scores_gemma":[0.00001794911,0.0001069627,0.0000153893,0.0004017634,0.00002293906,0.0003155762,0.00002904108,0.0001324653,0.000008184972],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007191592,"about_ca_system_score_gemma":0.0001138701,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1513877,"about_ca_topic_score_gemma":0.4690387,"domain_scores_codex":[0.9979322,0.00004046067,0.0005189308,0.0003029975,0.0006909989,0.0005144441],"domain_scores_gemma":[0.9990123,0.0001013801,0.00004536901,0.0005207677,0.000202576,0.0001176316],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002269578,0.0001075931,0.3754984,0.005961346,0.0003321728,0.0002272187,0.006987141,0.2366532,0.1216941,0.004448476,0.01441099,0.2334524],"study_design_scores_gemma":[0.0005722924,0.00009457426,0.8055645,0.003818687,0.00002101143,3.214746e-7,0.01225417,0.0051879,0.1304586,0.00000880631,0.04150304,0.000516057],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945716,0.00003019119,0.003786634,0.0001318072,0.0002627002,0.0005750739,0.0003197423,0.00004624372,0.0002760692],"genre_scores_gemma":[0.9946607,0.0001693112,0.004836987,0.00001059472,0.00006078689,0.0001012831,0.00003625199,0.00002235186,0.00010172],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4300661,"threshold_uncertainty_score":0.8542632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0646580470121118,"score_gpt":0.2978377481812209,"score_spread":0.2331797011691091,"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."}}