{"id":"W4372279159","doi":"10.3311/pptr.21926","title":"Dynamic Viscosity Prediction of Blends of Paving Grade Bitumen with Reclaimed Bitumen","year":2023,"lang":"en","type":"article","venue":"Periodica Polytechnica Transportation Engineering","topic":"Asphalt Pavement Performance Evaluation","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Transport Canada","funders":"Széchenyi István Egyetem; Budapesti Műszaki és Gazdaságtudományi Egyetem","keywords":"Asphalt; Softening point; Dynamic shear rheometer; Penetration test; Materials science; Penetration (warfare); Asphalt pavement; Rheology; Composite material; Rheometer; Sweep frequency response analysis; Rut; Environmental science; Geotechnical engineering; Engineering","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":[0.0003204064,0.0005625348,0.0003625609,0.001430289,0.0000990415,0.0004771947,0.0002940415,0.0003507691,0.0003624736],"category_scores_gemma":[0.0009177576,0.0002058694,0.000419136,0.0007018014,0.0001466982,0.0003969073,0.0002525067,0.0002670922,0.0002283398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003242098,"about_ca_system_score_gemma":0.0001321267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001903353,"about_ca_topic_score_gemma":0.001742702,"domain_scores_codex":[0.9995742,0.00004704268,0.00003452285,0.00008160176,0.0002128227,0.00004974454],"domain_scores_gemma":[0.9996389,0.0001115816,0.0001213468,0.00001987665,0.00008227839,0.00002604564],"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":[0.000680512,0.0002016754,0.04262668,0.0001805015,0.00008149417,0.0002295845,0.00007480915,0.01761049,0.8999051,0.0001347876,0.000100314,0.03817385],"study_design_scores_gemma":[0.00001164472,0.0007950453,0.07668909,0.00001952111,0.00009336168,0.000239647,0.00008713493,0.09723743,0.823841,0.00006461955,0.0008852808,0.00003611496],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.993632,0.0006608775,0.005063565,0.000009507827,0.00001052187,0.00001159671,0.00009410568,0.00007776186,0.0004399992],"genre_scores_gemma":[0.9972778,0.000313703,0.001872521,0.000002276339,0.000002585493,0.000005000393,0.000150619,0.00001206286,0.0003633976],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001903353,"threshold_uncertainty_score":0.003784537,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009305891643042815,"score_gpt":0.2127345344154161,"score_spread":0.2034286427723733,"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."}}