{"id":"W3151092510","doi":"10.3390/met11040583","title":"Predicting the External Corrosion Rate of X60 Pipeline Steel: A Mathematical Model","year":2021,"lang":"en","type":"article","venue":"Metals","topic":"Corrosion Behavior and Inhibition","field":"Materials Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Mitacs","keywords":"Cathodic protection; Corrosion; Coating; Service life; Sodium sulfate; Metallurgy; Salt (chemistry); Materials science; Sodium; Environmental science; Chemistry; Composite material; Anode","routes":{"ca_aff":true,"ca_fund":true,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008606695,0.00009015039,0.0001963815,0.00002081925,0.00009283295,0.00005077051,0.0001311736,0.00004007998,0.001306804],"category_scores_gemma":[0.0002021967,0.00005722606,0.00009196084,0.00009726479,0.00005972054,0.000142514,0.0001277899,0.00007668052,0.0001067204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001354708,"about_ca_system_score_gemma":0.00004122303,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004027294,"about_ca_topic_score_gemma":0.000003417833,"domain_scores_codex":[0.9988902,0.0001410155,0.0003833211,0.000184405,0.0002527536,0.0001483364],"domain_scores_gemma":[0.9992869,0.000107278,0.0001330849,0.0002896538,0.0001398366,0.00004327853],"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":[0.00001364058,0.0000776585,0.0000483522,0.00002096676,2.382226e-7,0.000002894999,0.0002220779,0.001034033,0.9973236,0.0007347183,0.0003033184,0.000218468],"study_design_scores_gemma":[0.0001699342,0.00001714026,0.00005690594,0.00008770157,0.00004894732,0.00002030253,0.00008976232,0.1305021,0.8668049,0.002107777,0.00003784554,0.00005665033],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8214788,0.0001268554,0.1774537,0.000174024,0.0001338226,0.0001053947,0.00003099664,0.0000319454,0.0004644298],"genre_scores_gemma":[0.9938495,0.00001020083,0.00361544,0.0001466953,0.00005335889,0.00001661655,0.000005151976,0.00001088673,0.002292144],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1738383,"threshold_uncertainty_score":0.9996061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03823816187147727,"score_gpt":0.2871822337823932,"score_spread":0.2489440719109159,"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."}}