{"id":"W2096197076","doi":"10.1061/41173(414)4","title":"Sampling and Condition Assessment of Ductile Iron Pipes","year":2011,"lang":"en","type":"article","venue":"World Environmental and Water Resources Congress 2011","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Corrosion; Ductile iron; Sampling (signal processing); Probabilistic logic; Geotechnical engineering; Materials science; Geology; Metallurgy; Cast iron; Engineering; Mathematics; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005697922,0.0003141302,0.0004704619,0.001204733,0.0005853957,0.0002812353,0.0005622408,0.000438074,0.000573216],"category_scores_gemma":[0.001450993,0.0003028582,0.0001881887,0.0009442304,0.0005045632,0.0002820249,0.0005552327,0.000283069,0.0001275422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003178035,"about_ca_system_score_gemma":0.0002940928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005582122,"about_ca_topic_score_gemma":0.01112667,"domain_scores_codex":[0.9993922,0.00009225516,0.00003928071,0.0001948094,0.0002274038,0.00005401587],"domain_scores_gemma":[0.999241,0.0001622451,0.0001780962,0.00009246738,0.000289787,0.00003646887],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0008044561,0.0003862753,0.3501493,0.0001924325,0.00004739465,0.00115078,0.002674261,0.02232279,0.5629431,0.000409895,0.0002359436,0.05868341],"study_design_scores_gemma":[0.00003109576,0.0009916675,0.810319,0.00001476873,0.00004590793,0.0005505089,0.0008644921,0.04863705,0.1367708,0.000294604,0.001436323,0.00004381493],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9802352,0.00002279768,0.01877578,0.000005792707,0.000001359921,0.0001138335,0.0002441538,0.00005809323,0.0005429252],"genre_scores_gemma":[0.9808188,0.00005110246,0.01802937,0.000005304288,0.000003338202,0.0001194341,0.000318452,0.00001328457,0.000640734],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005582122,"threshold_uncertainty_score":0.01109928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009025338089216238,"score_gpt":0.196302821411935,"score_spread":0.1872774833227188,"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."}}