{"id":"W2229300237","doi":"10.1061/(asce)mt.1943-5533.0001492","title":"Rational Mix-Design Procedure for Cold In-Place Recycling Asphalt Mixtures and Performance Prediction","year":2016,"lang":"en","type":"article","venue":"Journal of Materials in Civil Engineering","topic":"Asphalt Pavement Performance Evaluation","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Federal Highway Administration; University of Illinois at Urbana-Champaign; State of Connecticut Department of Transportation","keywords":"Asphalt; Ultimate tensile strength; Creep; Asphalt pavement; Cracking; Aggregate (composite); Engineering; Civil engineering; Fatigue cracking; Waste management; Rut; Geotechnical engineering; Environmental science; Materials science; Composite material","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":[],"consensus_categories":[],"category_scores_codex":[0.001277665,0.0001434518,0.0002320534,0.0003539338,0.00002123326,0.00003351467,0.00008270563,0.00009213559,0.0000267931],"category_scores_gemma":[0.0001608024,0.0001174655,0.00002039153,0.00012193,0.000008542514,0.000743475,0.0000106919,0.00009392615,0.000001075818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001972196,"about_ca_system_score_gemma":0.00003908208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":2.826278e-7,"about_ca_topic_score_gemma":0.000003142915,"domain_scores_codex":[0.9988304,0.00002052951,0.0006384784,0.00009955876,0.0002015102,0.0002095694],"domain_scores_gemma":[0.9995438,0.0001613486,0.0001272101,0.00006217797,0.00006463974,0.0000407863],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00007058368,0.000009357966,0.00119955,0.0003224654,0.0000134962,0.000001294921,0.0001014717,0.4167933,0.5808933,0.00001901192,0.0001471349,0.0004290141],"study_design_scores_gemma":[0.00216117,0.0002207399,0.01297261,0.001512751,0.00001779322,0.00003536441,0.00001461634,0.2085478,0.7739887,0.00005104249,0.0002758436,0.0002015101],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9464629,0.0003670075,0.05173508,0.0000593812,0.0009956141,0.0003254927,0.000009773607,0.00003488229,0.000009888214],"genre_scores_gemma":[0.9936798,0.0007688404,0.005076302,0.000007305639,0.0003649049,0.00005367428,0.00000186331,0.00003141,0.00001586455],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2082455,"threshold_uncertainty_score":0.4790104,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01486937235647153,"score_gpt":0.2267700078279459,"score_spread":0.2119006354714744,"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."}}