{"id":"W3134648949","doi":"10.21203/rs.3.rs-265319/v1","title":"Constitutive Modeling for Prediction of Optimal Process Parameters in Tribo-corrosion Inhibition of Steel Pipes Carrying Fracking Fluid","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Corrosion Behavior and Inhibition","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Materials science; Corrosion; Response surface methodology; Metallurgy; Reciprocating motion; Tribometer; Quadratic model; Composite material; Tribology; Mechanical engineering; Mathematics; Statistics","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":[0.0008077387,0.0006507756,0.0006161606,0.0006118311,0.0002716574,0.000748392,0.0006551036,0.001537427,0.001014541],"category_scores_gemma":[0.001216485,0.0004869553,0.0007912061,0.0003631621,0.0003831358,0.000347752,0.0002612723,0.0005310152,0.0003177329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008063248,"about_ca_system_score_gemma":0.000974241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007156159,"about_ca_topic_score_gemma":0.005435075,"domain_scores_codex":[0.9997628,0.00004587316,0.00001707084,0.0000480128,0.00009187445,0.00003429589],"domain_scores_gemma":[0.9996276,0.0001904615,0.0000751158,0.00002518272,0.00007221652,0.000009449296],"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":[0.00001959045,0.0000576861,0.0007564169,0.00005550518,0.00001021568,0.00004150559,0.00002756845,0.971244,0.02326568,0.0006176634,0.00006413361,0.003840107],"study_design_scores_gemma":[0.000001129204,0.000009519869,0.0001638778,0.000002034539,0.000002369823,0.000003482686,0.000003325831,0.9976782,0.00197007,0.00005369386,0.0001103606,0.000001841218],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4350753,0.001335585,0.5550582,0.0002734211,0.00005594856,0.0001773603,0.0003777776,0.000543214,0.007103154],"genre_scores_gemma":[0.9830071,0.0003925984,0.01444725,0.00001338551,0.00000475691,0.0001403642,0.0001003156,0.00004053357,0.001853704],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007156159,"threshold_uncertainty_score":0.014229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1170949553121409,"score_gpt":0.3931485044384139,"score_spread":0.276053549126273,"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."}}