{"id":"W748766242","doi":"","title":"MODELING FLEXIBLE PAVEMENT PERFORMANCE USING CANADIAN HISTORIC DATA","year":2002,"lang":"en","type":"article","venue":"Ninth International Conference on Asphalt PavementsInternational Society for Asphalt Pavements","topic":"Asphalt Pavement Performance Evaluation","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pavement management; Christian ministry; Transport engineering; Engineering; Range (aeronautics); Judgement; Civil engineering; Process (computing); Computer science; Operations research","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001009321,0.0007580938,0.0004555148,0.0004693414,0.0006275396,0.0003375905,0.002168283,0.0002526549,0.005564156],"category_scores_gemma":[0.00005179327,0.0008663518,0.0003608056,0.0003528229,0.00008995587,0.001853915,0.0002763786,0.0005157191,0.0003276403],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003060489,"about_ca_system_score_gemma":0.0002101224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001518514,"about_ca_topic_score_gemma":0.0006773371,"domain_scores_codex":[0.9941896,0.00003890076,0.001305765,0.001130699,0.002156488,0.001178524],"domain_scores_gemma":[0.9973522,0.00005868925,0.0002899894,0.0009617365,0.0008474012,0.0004899523],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001109353,0.001180218,0.006438067,0.0005665674,0.004961069,0.00001217372,0.002157029,0.8631217,0.004616043,0.009669939,0.04719081,0.05997545],"study_design_scores_gemma":[0.002386579,0.0001712728,0.0001610766,0.0002458401,0.0001094059,0.00000531262,0.0002231482,0.9712427,0.001352871,0.0002327355,0.02308522,0.0007837995],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5378972,0.001053131,0.3619284,0.003188312,0.02622731,0.00692341,0.005180825,0.001696671,0.05590468],"genre_scores_gemma":[0.978421,0.0007337574,0.01132301,0.001604271,0.0008958073,0.0003640801,0.002916224,0.0001572318,0.003584597],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4405238,"threshold_uncertainty_score":0.9993787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2099299876121588,"score_gpt":0.3311857532575138,"score_spread":0.121255765645355,"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."}}