{"id":"W604897755","doi":"","title":"Impact Analysis of Individual Distresses on Overall Pavement Condition Assessment","year":2008,"lang":"en","type":"article","venue":"","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Rut; Scale (ratio); Process (computing); International Roughness Index; Rating scale; Distress; Engineering; Computer science; Asphalt; Statistics; Surface finish; Mathematics; Mechanical engineering; Psychology; 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":[0.003099594,0.0006414824,0.0004924705,0.001788316,0.00036532,0.0007447323,0.0003515847,0.0003428341,0.002993354],"category_scores_gemma":[0.01185276,0.0001631399,0.0006093006,0.001516177,0.0005387574,0.0006579502,0.0008291234,0.0003902261,0.0003194051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00153212,"about_ca_system_score_gemma":0.0006089647,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03037048,"about_ca_topic_score_gemma":0.06146825,"domain_scores_codex":[0.9963706,0.001025846,0.0001463339,0.0003059699,0.001895068,0.000256235],"domain_scores_gemma":[0.987918,0.005995974,0.001656634,0.0007337015,0.00319323,0.0005025467],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002847713,0.0003641869,0.6984584,0.0004060989,0.0004123658,0.0004905658,0.001039723,0.05923617,0.02756922,0.0004926362,0.001418253,0.2072648],"study_design_scores_gemma":[0.00001495772,0.001855402,0.9557129,0.00002567058,0.0001780081,0.0001319173,0.001071783,0.03259518,0.006923612,0.0002143918,0.001232877,0.00004337854],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9863151,0.0002874127,0.008008413,0.00007189067,0.0000158651,0.000125369,0.0008677531,0.0001289599,0.004179219],"genre_scores_gemma":[0.9971494,0.00007373667,0.001825857,0.000009954403,0.000003697562,0.00001311819,0.0002796649,0.000009766859,0.0006348205],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03037048,"threshold_uncertainty_score":0.06038737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01194719576600095,"score_gpt":0.2791338966681262,"score_spread":0.2671867009021252,"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."}}