{"id":"W1921183443","doi":"10.1139/cjce-2015-0156","title":"Quantification and comparison of carbon emissions for flexible underground pipelines","year":2015,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Underground infrastructure and sustainability","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pipeline transport; Carbon footprint; Greenhouse gas; Pipeline (software); Life-cycle assessment; Polyvinyl chloride; Environmental science; Waste management; Carbon steel; Carbon dioxide; Engineering; Environmental engineering; Process engineering; Materials science; Production (economics); Corrosion; Mechanical engineering; Geology; Metallurgy; Composite material","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002304063,0.0001036555,0.0002377018,0.0002312029,0.00002783402,0.0000298275,0.00009422786,0.00007203354,0.000006874778],"category_scores_gemma":[0.0002484102,0.0001032344,0.00004460901,0.0001361411,0.00002758924,0.0001326589,0.000003718274,0.0001318699,7.045232e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000177877,"about_ca_system_score_gemma":0.0003314238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003059538,"about_ca_topic_score_gemma":0.009986842,"domain_scores_codex":[0.9992835,0.000006955961,0.0003705539,0.00006188553,0.00008772295,0.0001893753],"domain_scores_gemma":[0.9991046,0.00006824624,0.00006706725,0.0001046382,0.0002491213,0.0004063935],"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":[0.00001657731,0.00001137412,0.01271584,0.0005289097,0.0001010678,0.000004777009,0.002302574,0.9672055,0.005715193,0.002898365,0.006827895,0.001671916],"study_design_scores_gemma":[0.001811129,0.0004158044,0.01050839,0.0003511776,0.000179589,0.0001397308,0.005326595,0.8738263,0.0107326,0.0152329,0.08074563,0.0007301237],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6068696,0.007489204,0.3801652,0.0002993821,0.00164682,0.0002592283,0.00001676524,0.00006856339,0.003185302],"genre_scores_gemma":[0.9986643,0.00000974791,0.001148815,0.000003896671,0.0001173425,0.000001850711,0.000002540574,0.00002023312,0.00003128014],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3917947,"threshold_uncertainty_score":0.5572892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0266373260887985,"score_gpt":0.2511465677229489,"score_spread":0.2245092416341504,"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."}}