{"id":"W7100769246","doi":"","title":"AN EVALUATION OF VARIOUS PRIORITIZATION METHODS FOR EFFECTIVE PAVEMENT MANAGEMENT: A CANADIAN AIRPORT CASE STUDY By:","year":2004,"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":"Prioritization; Ranking (information retrieval); Pavement management; Test (biology); Management by objectives; Current (fluid)","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":[0.01085092,0.001276651,0.0007521434,0.005065497,0.003549708,0.002875171,0.001748648,0.001217418,0.002680983],"category_scores_gemma":[0.01733737,0.0004225451,0.0008479915,0.005116576,0.001348177,0.001409177,0.001058123,0.0008395679,0.0001892561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02796096,"about_ca_system_score_gemma":0.01996485,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6268806,"about_ca_topic_score_gemma":0.7206112,"domain_scores_codex":[0.9927383,0.002875639,0.0003196006,0.0003179004,0.003089365,0.0006590884],"domain_scores_gemma":[0.9882393,0.006030793,0.0004458692,0.000389089,0.004420214,0.000474717],"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":[0.002026241,0.004305301,0.05688529,0.002112416,0.0002882523,0.002284559,0.006719817,0.2554249,0.0107945,0.03682131,0.01768267,0.6046547],"study_design_scores_gemma":[0.0009913329,0.004283976,0.09217647,0.0007035925,0.0006837341,0.001021454,0.02094752,0.8108676,0.01624563,0.007018912,0.04456456,0.0004952148],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8840517,0.002372826,0.05828018,0.002424982,0.00007927482,0.004329196,0.001029366,0.0002589012,0.04717349],"genre_scores_gemma":[0.8643996,0.001301497,0.1294141,0.0001113061,0.00001561923,0.0005629718,0.0004071858,0.0000502486,0.003737376],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3731194,"threshold_uncertainty_score":0.7506336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01133538179402593,"score_gpt":0.3337582967720502,"score_spread":0.3224229149780243,"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."}}