{"id":"W102034023","doi":"","title":"Potential Use of Friction Data from LTPP Database in Preliminary Maintenance Decisions for Asphalt and Concrete Pavements","year":2015,"lang":"en","type":"article","venue":"Transportation Research Board 94th Annual MeetingTransportation Research Board","topic":"Asphalt Pavement Performance Evaluation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Database; Asphalt concrete; Asphalt; Axle; Engineering; Environmental science; Computer science; Structural engineering; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005801886,0.0004767644,0.0008869443,0.00700982,0.0004817106,0.002295204,0.001395374,0.0006829639,0.001058155],"category_scores_gemma":[0.030038,0.0004447588,0.0005975435,0.005727927,0.0001938648,0.001711242,0.000786741,0.0004453712,0.0005205793],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002250736,"about_ca_system_score_gemma":0.001151068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02982244,"about_ca_topic_score_gemma":0.04604774,"domain_scores_codex":[0.9947169,0.001320556,0.0005705555,0.0006147305,0.002475352,0.0003018196],"domain_scores_gemma":[0.9754788,0.01044125,0.003936118,0.002686551,0.006968925,0.000488329],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001109587,0.0003091343,0.7665176,0.0004575147,0.0002555039,0.000751449,0.0009089144,0.02548611,0.005337994,0.001146763,0.005046087,0.1926734],"study_design_scores_gemma":[0.00005510369,0.0004564277,0.8624467,0.0003135691,0.0002574652,0.0006180878,0.001727928,0.110429,0.009525184,0.00106906,0.01296018,0.0001412593],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9539602,0.0009044113,0.01196321,0.0004798903,0.00003683575,0.0003146716,0.02119647,0.0009358385,0.01020854],"genre_scores_gemma":[0.9797969,0.0002061441,0.01025878,0.00004257998,0.000009228751,0.00006756785,0.009094464,0.00003299715,0.0004914177],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02982244,"threshold_uncertainty_score":0.05929768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2033171476615622,"score_gpt":0.4016820176153383,"score_spread":0.1983648699537761,"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."}}