{"id":"W4385722968","doi":"10.1061/9780784485026.048","title":"Decision Making Process for the Sewer Pipe Liner Evaluation","year":2023,"lang":"en","type":"article","venue":"","topic":"Geotechnical Engineering and Underground Structures","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Stantec (Canada)","funders":"","keywords":"Sanitary sewer; Pipeline transport; Trenchless technology; Pipeline (software); Rehabilitation; Modernization theory; Engineering; Process (computing); Service (business); Construction engineering; Civil engineering; Risk analysis (engineering); Computer science; Business; Environmental engineering; Mechanical engineering; Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.02844611,0.001341299,0.001866865,0.002559419,0.00256034,0.006309845,0.002554145,0.002355987,0.01675626],"category_scores_gemma":[0.03839231,0.0007283151,0.001368794,0.001939719,0.001545733,0.002717546,0.002518714,0.002924376,0.001759801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005321925,"about_ca_system_score_gemma":0.01608284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00387702,"about_ca_topic_score_gemma":0.004903267,"domain_scores_codex":[0.9749503,0.01766209,0.0009657071,0.001233107,0.004017239,0.001171508],"domain_scores_gemma":[0.9658544,0.02531032,0.001638426,0.0008532641,0.00533403,0.001009528],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001192309,0.001503347,0.004755061,0.001115813,0.0002733618,0.001012188,0.004127441,0.5507201,0.006595172,0.1496449,0.007051673,0.2720086],"study_design_scores_gemma":[0.0002713951,0.0007567148,0.001584386,0.0004491295,0.0001173262,0.00009031673,0.002408955,0.8633928,0.00636452,0.1063279,0.01810429,0.0001322934],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0642238,0.0003494838,0.8997978,0.002027399,0.00009049533,0.00788254,0.0006908584,0.0003269926,0.02461056],"genre_scores_gemma":[0.2761802,0.0002840413,0.7163483,0.0001970051,0.0000431672,0.003670318,0.000455958,0.00005219905,0.002768804],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02844611,"threshold_uncertainty_score":0.1504392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02633020192150399,"score_gpt":0.3091787484333839,"score_spread":0.2828485465118799,"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."}}