{"id":"W4405361979","doi":"10.1115/ipc2024-134150","title":"Experimental and Statistical Analyses of the Tribological and Weathering Behaviors of Pipeline Support Materials","year":2024,"lang":"en","type":"article","venue":"Volume 3: Operations, Monitoring, and Maintenance; Materials and Joining","topic":"Mechanical stress and fatigue analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nova Chemicals (Canada)","funders":"","keywords":"Weathering; Tribology; Pipeline (software); Statistical analysis; Materials science; Computer science; Geology; Metallurgy; Geochemistry; Statistics; Mathematics","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":[0.001439325,0.0003916638,0.0003556439,0.001726156,0.000439384,0.0002324919,0.0003342649,0.0003167834,0.002457093],"category_scores_gemma":[0.003413543,0.0001574309,0.0004278283,0.001428132,0.000452922,0.0003407985,0.0002827974,0.0002629423,0.0003373977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001898012,"about_ca_system_score_gemma":0.0001422519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007518346,"about_ca_topic_score_gemma":0.001079849,"domain_scores_codex":[0.9983838,0.0002240185,0.0002103219,0.0003602477,0.0006949776,0.0001267948],"domain_scores_gemma":[0.9951842,0.001671265,0.0007558426,0.0006073836,0.001657976,0.0001233813],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001432497,0.0007235939,0.1260251,0.0005223837,0.0001720655,0.0002006455,0.0003184329,0.009790991,0.7848511,0.0003413209,0.0006344786,0.07498738],"study_design_scores_gemma":[0.00001721034,0.003592845,0.4699223,0.00001764868,0.0001336053,0.0003461124,0.0004855908,0.02335368,0.4993943,0.0002035806,0.002475118,0.00005807135],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9921468,0.000212525,0.00575333,0.000007938524,0.00001616194,0.00006320327,0.0007258253,0.00004890701,0.001025264],"genre_scores_gemma":[0.9963452,0.00005149142,0.002500587,0.000003303278,0.000004591823,0.00006387795,0.0006179182,0.00001179646,0.0004011613],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002457093,"threshold_uncertainty_score":0.008219779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02770330433086405,"score_gpt":0.2975353503455558,"score_spread":0.2698320460146917,"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."}}