{"id":"W2067308808","doi":"10.1080/10298430410001672246","title":"Stochastic Modeling of Pavement Performance","year":2003,"lang":"en","type":"article","venue":"International Journal of Pavement Engineering","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":72,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Probabilistic logic; Markov chain; Stochastic matrix; Engineering; Markov process; Pavement engineering; Transformation (genetics); Computer science; Mathematics; Statistics; Materials science","routes":{"ca_aff":false,"ca_fund":true,"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":[0.0006217595,0.0007839985,0.0006370264,0.0005876909,0.00030439,0.0008924609,0.00150262,0.0009734311,0.001538767],"category_scores_gemma":[0.002423491,0.0004148319,0.000591584,0.000716526,0.0009347177,0.001041285,0.0005470192,0.0006449819,0.0003987595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001359308,"about_ca_system_score_gemma":0.0008860573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0182583,"about_ca_topic_score_gemma":0.0109358,"domain_scores_codex":[0.9992595,0.0001432357,0.00003037384,0.0001774695,0.00026097,0.0001284313],"domain_scores_gemma":[0.9992319,0.0003021689,0.0001921879,0.00009982754,0.0001338261,0.00004018101],"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":[0.000007851678,0.000008303613,0.0005010539,0.000009605885,0.000006689573,0.00002087916,0.00001306172,0.9890723,0.0007043718,0.007607974,0.00009546529,0.001952421],"study_design_scores_gemma":[0.000002047964,0.000007732782,0.0004933164,0.000001452905,0.000003515939,0.000008369188,0.000002667728,0.9963928,0.0001630049,0.002724626,0.0001956333,0.000004820848],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.194981,0.00041123,0.7916248,0.0003595179,0.00005517142,0.00009447781,0.0008615028,0.0005878439,0.01102428],"genre_scores_gemma":[0.9859002,0.000324457,0.008763205,0.00001446992,0.00002879763,0.00006810899,0.0002528378,0.0000312373,0.004616694],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0182583,"threshold_uncertainty_score":0.03630406,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007219446309390771,"score_gpt":0.2054263841969459,"score_spread":0.1982069378875551,"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."}}