{"id":"W2765914002","doi":"10.1115/pvp2017-65236","title":"Expression of a Generic Full-Range True Stress-True Strain Model for Pipeline Steels Using the Product-Log (Omega) Function","year":2017,"lang":"en","type":"article","venue":"","topic":"Fatigue and fracture mechanics","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"TransCanada (Canada); University of Alberta","funders":"","keywords":"Pipeline (software); Stress (linguistics); Pipeline transport; Range (aeronautics); Deformation (meteorology); Structural engineering; Function (biology); Stress–strain curve; Strain (injury); Characterization (materials science); Computer science; Materials science; Mechanical engineering; Engineering; Composite material","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000206911,0.0001660023,0.0001892487,0.0000489074,0.0002087064,0.00005151355,0.0002590307,0.00008794564,0.00002207293],"category_scores_gemma":[0.00005692096,0.0001118292,0.00008015161,0.00004554732,0.00002743411,0.0002402589,0.00004265501,0.0001187045,0.00000112356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002285877,"about_ca_system_score_gemma":0.00002107164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001597084,"about_ca_topic_score_gemma":0.00006187207,"domain_scores_codex":[0.9991826,0.00001297707,0.0002333648,0.000195076,0.0001561486,0.0002198429],"domain_scores_gemma":[0.9990709,0.00002744462,0.0001087071,0.0006758855,0.00007635873,0.0000407356],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004484753,0.0000246924,0.00002329944,0.0001514402,0.00001809291,3.606469e-7,0.0002673967,0.4860705,0.5040354,0.0002941875,0.0008845981,0.008185116],"study_design_scores_gemma":[0.0003223032,0.00003204891,0.0000621717,0.00004218447,0.00003825409,0.000001286484,0.00009327983,0.8690264,0.1294785,0.0005205258,0.0002543066,0.0001287429],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1362007,0.0002582072,0.8620153,0.00008813715,0.0004820069,0.0004366988,0.0001015902,0.00007782748,0.0003395579],"genre_scores_gemma":[0.9874468,0.00002584758,0.01175162,0.00002849668,0.0002972352,0.00003130929,0.0000225091,0.00003864691,0.0003575546],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8512461,"threshold_uncertainty_score":0.4560262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05031910325954309,"score_gpt":0.2602090047434362,"score_spread":0.2098899014838931,"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."}}