{"id":"W2760967282","doi":"10.1520/jte20160263","title":"Laboratory Investigations of Cold Mix Asphalt for Cold Region Applications","year":2017,"lang":"en","type":"article","venue":"Journal of Testing and Evaluation","topic":"Asphalt Pavement Performance Evaluation","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Canadian Natural Resources","funders":"","keywords":"Asphalt; Durability; Asphalt pavement; Environmental science; Aggregate (composite); Ultimate tensile strength; Cohesion (chemistry); Forensic engineering; Materials science; Engineering; Composite material","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001767276,0.00007556201,0.0001380029,0.0001035765,0.0002525259,0.00005731426,0.0001134724,0.00005073417,0.000002522965],"category_scores_gemma":[0.001267552,0.0000761309,0.00002862446,0.00009188243,0.00005157194,0.0005666747,0.00001050072,0.00008602555,0.000001188554],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000781702,"about_ca_system_score_gemma":0.0001423195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002742102,"about_ca_topic_score_gemma":0.000002869361,"domain_scores_codex":[0.9990755,0.0000270485,0.0004310549,0.00006818883,0.0003079301,0.00009030315],"domain_scores_gemma":[0.9977539,0.0002092973,0.0006629284,0.0001750358,0.001143275,0.00005559521],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004140454,0.0001602179,0.1110369,0.001349837,0.0002548645,0.000001077925,0.0009107576,0.2678307,0.4660279,0.002340013,0.009002213,0.1410441],"study_design_scores_gemma":[0.002229731,0.0003518918,0.05010477,0.0006629085,0.0004255553,0.00001064425,0.000114712,0.8860283,0.05508372,0.002516573,0.002266877,0.0002043073],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9742948,0.0007951118,0.02311387,0.0002839706,0.0002831187,0.0007226951,0.000009036762,0.0000269887,0.0004703582],"genre_scores_gemma":[0.981039,0.00005894133,0.01853338,0.00001622134,0.0002356371,0.00007868002,0.000003561834,0.00001272129,0.00002187623],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6181976,"threshold_uncertainty_score":0.3104528,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09649453145985515,"score_gpt":0.330203698244949,"score_spread":0.2337091667850938,"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."}}