{"id":"W3156669627","doi":"10.22215/etd/2019-13737","title":"Technical and Economic Development of Efficient Asphalt Multi-Integrated Compaction Technology","year":2019,"lang":"en","type":"dissertation","venue":"","topic":"Asphalt Pavement Performance Evaluation","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Compaction; Asphalt; Engineering; Civil engineering; Asphalt pavement; Geotechnical engineering; Bridge deck; Forensic engineering; Deck; Materials science; Structural engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001722856,0.00023205,0.000322311,0.0004423903,0.00003552657,0.00001035901,0.0001048584,0.0003847292,0.000159818],"category_scores_gemma":[0.000008226516,0.0002272821,0.00002945394,0.0001230414,0.00001999621,0.00005586501,0.00001348114,0.0002465973,0.0001360152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003947673,"about_ca_system_score_gemma":0.0001385986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008684296,"about_ca_topic_score_gemma":0.000261443,"domain_scores_codex":[0.9989474,0.000007055264,0.0005257484,0.0002143367,0.0001318867,0.0001735178],"domain_scores_gemma":[0.9995812,0.00001525372,0.000135626,0.0001731536,0.00006382901,0.00003092817],"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":[0.0001752441,0.0003333481,0.004760237,0.003479409,0.0005221476,0.000001339701,0.002101863,0.3497445,0.3609105,0.001184141,0.0008460872,0.2759413],"study_design_scores_gemma":[0.0007541891,0.00005217896,0.0149997,0.000239634,0.00005219711,0.000002543942,0.001054412,0.7320373,0.2496478,0.000004792376,0.0007640903,0.0003911592],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9769704,0.000273354,0.01768319,0.000004716885,0.0007941001,0.0006112374,0.000006538336,0.0003464398,0.003310053],"genre_scores_gemma":[0.9847634,0.00005053915,0.01365896,0.000001831205,0.00001126146,0.00005489047,0.0005950253,0.00004118236,0.0008229481],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3822928,"threshold_uncertainty_score":0.9268296,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01480331068273088,"score_gpt":0.2721310700352476,"score_spread":0.2573277593525167,"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."}}