{"id":"W2883414739","doi":"10.1038/s41524-018-0089-4","title":"Phase-field model of pitting corrosion kinetics in metallic materials","year":2018,"lang":"en","type":"article","venue":"npj Computational Materials","topic":"Aluminum Alloy Microstructure Properties","field":"Engineering","cited_by":114,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Hong Kong Polytechnic University; Research Grants Council, University Grants Committee","keywords":"Materials science; Corrosion; Electrolyte; Overpotential; Pitting corrosion; Phase (matter); Kinetic energy; Metallurgy; Metal; Ceramic; Thermodynamics; Electrochemistry; Composite material; Chemistry; Physical chemistry; Electrode; Physics","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":[0.0001967129,0.0001659667,0.0003185982,0.0001147624,0.00002788448,0.00004942817,0.0001522205,0.00009386759,0.0003953723],"category_scores_gemma":[0.00005197665,0.0001590714,0.00002295587,0.00008935394,0.00006598853,0.0001164426,0.00005936328,0.00004126498,0.00003298546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003950785,"about_ca_system_score_gemma":0.00002032116,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001649352,"about_ca_topic_score_gemma":0.000003959171,"domain_scores_codex":[0.9988514,0.00004100757,0.0005778531,0.000157628,0.0001784139,0.0001936806],"domain_scores_gemma":[0.9995721,0.00006446846,0.00009565912,0.0001209016,0.000117755,0.00002911881],"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":[0.00005804681,0.00003493811,0.00000674194,0.00009469425,0.00001017589,7.469778e-7,0.0003226867,0.04132653,0.9571893,0.0005973607,0.0001141337,0.000244627],"study_design_scores_gemma":[0.0006466851,0.0001435419,0.0001090037,0.00007027325,0.00001158159,0.000005234947,0.00001379162,0.03739721,0.9560919,0.005330908,0.00002576621,0.0001540789],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9821231,0.00004414283,0.01660465,0.00002508634,0.0006865257,0.0001815206,0.000095572,0.00009006132,0.0001493857],"genre_scores_gemma":[0.9819899,0.000005105061,0.01765204,0.00006566504,0.0001639359,0.00001262855,0.00005514859,0.00003804885,0.00001758466],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004733548,"threshold_uncertainty_score":0.6486742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01920476237928089,"score_gpt":0.2506031446960762,"score_spread":0.2313983823167953,"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."}}