{"id":"W2949328995","doi":"10.1201/9780203865286-111","title":"Pavement base unbound granular materials gradation optimization","year":2009,"lang":"en","type":"book-chapter","venue":"","topic":"Asphalt Pavement Performance Evaluation","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Gradation; Base (topology); Granular material; Materials science; Composite material; Computer science; Mathematics; Artificial intelligence","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":[0.0004216688,0.001206036,0.0007769942,0.001476962,0.0005053571,0.001354389,0.00105372,0.0006937535,0.007189879],"category_scores_gemma":[0.0006812653,0.0003085327,0.0005194014,0.0009774584,0.0003346048,0.0004294487,0.0005746656,0.0006367487,0.001203861],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001717534,"about_ca_system_score_gemma":0.0008806508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02641973,"about_ca_topic_score_gemma":0.07047685,"domain_scores_codex":[0.9997271,0.00001732794,0.00000845236,0.00005093227,0.0001072749,0.0000889832],"domain_scores_gemma":[0.9997486,0.00003531054,0.00001964806,0.00003135598,0.0001321474,0.00003290363],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005481494,0.0007391762,0.006981577,0.000394623,0.00004884382,0.0003506796,0.00007452254,0.7719513,0.1176357,0.001301484,0.003128462,0.09684552],"study_design_scores_gemma":[0.0001027737,0.001516801,0.03145326,0.00005325313,0.0001911998,0.0001831407,0.0004571861,0.8403406,0.1067922,0.0009217403,0.01791006,0.00007765285],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9171869,0.0005098809,0.04884607,0.00007982165,0.00005403857,0.0003792009,0.001165104,0.001068149,0.03071084],"genre_scores_gemma":[0.974178,0.0001162907,0.01738824,0.00002367896,0.000002424986,0.000085387,0.0006877452,0.0001306593,0.007387494],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.02641973,"threshold_uncertainty_score":0.0525319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0191918973490217,"score_gpt":0.2198090233493039,"score_spread":0.2006171260002822,"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."}}