{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007436969,0.0006117707,0.0002872172,0.0005842525,0.0005438342,0.0003614358,0.0004712727,0.0003919231,0.0007439652],"category_scores_gemma":[0.000945934,0.000171539,0.0004102601,0.0003911915,0.000309088,0.0003152385,0.0003284565,0.0003637398,0.0002180501],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002704044,"about_ca_system_score_gemma":0.0002477674,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001283071,"about_ca_topic_score_gemma":0.002736813,"domain_scores_codex":[0.999328,0.0001188581,0.00006270115,0.0001398502,0.000285247,0.0000654675],"domain_scores_gemma":[0.999023,0.0001924734,0.0002231738,0.0001006762,0.0003797336,0.00008095334],"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":[0.0002223565,0.0004316897,0.006922053,0.0001050672,0.00002168479,0.00009741126,0.0001805067,0.0008858761,0.9871775,0.0000480065,0.00004627129,0.003861664],"study_design_scores_gemma":[0.00001884863,0.00801715,0.02350832,0.00001322581,0.00009153711,0.0002124023,0.0003378185,0.001798137,0.9652466,0.00004716814,0.0006900881,0.00001865667],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976614,0.0001076708,0.001705269,0.000006795628,0.000007583102,0.00004887745,0.0001235963,0.00001714819,0.0003216018],"genre_scores_gemma":[0.9966273,0.0001193493,0.002590424,0.00000951425,0.000006678915,0.00005007114,0.0001488506,0.000005683841,0.0004422506],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001283071,"threshold_uncertainty_score":0.003933132,"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."}}