{"id":"W4322741659","doi":"10.3390/met13030494","title":"Preparation of Tannic Acid/Hyaluronic Acid Coating to Improve the Corrosion Resistance of Implant Material Based on AZ31B Magnesium Alloy","year":2023,"lang":"en","type":"article","venue":"Metals","topic":"Magnesium Alloys: Properties and Applications","field":"Materials Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Corrosion; Magnesium; Tannic acid; Coating; Biocompatibility; Magnesium alloy; Tafel equation; Materials science; Metallurgy; Nuclear chemistry; Alloy; Hyaluronic acid; Chemistry; Chemical engineering; Composite material; Organic chemistry; Electrochemistry","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":[0.001019786,0.0001576563,0.0002805867,0.00007179003,0.0001597977,0.00005626402,0.0004071481,0.00005696203,0.0004095079],"category_scores_gemma":[0.0001382414,0.0001052204,0.00007695852,0.0003315936,0.00007816214,0.0000963014,0.0001235904,0.00004911596,0.0001864654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003263207,"about_ca_system_score_gemma":0.00007115165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007259257,"about_ca_topic_score_gemma":0.00008600103,"domain_scores_codex":[0.9982932,0.0001475733,0.0005453615,0.0003464283,0.0003893539,0.000278119],"domain_scores_gemma":[0.9987709,0.00008842974,0.0003205873,0.0006456515,0.0001218869,0.00005255334],"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":[0.0002828157,0.00003967457,0.000006488753,0.0001207752,0.000001450491,5.402611e-7,0.0001832468,0.0006901955,0.9966659,0.0005233462,0.001330973,0.0001545902],"study_design_scores_gemma":[0.0002227316,0.0003280449,0.0003495943,0.00003163873,0.00003400599,7.477659e-7,0.00009658687,0.002553951,0.994141,0.00007631646,0.002045344,0.0001199673],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961887,0.00004183362,0.0005546667,0.001054446,0.0004357178,0.0008529254,0.0002831506,0.00008222571,0.0005063146],"genre_scores_gemma":[0.9967554,0.000003401327,0.001138643,0.0001665307,0.00007672948,0.0002902162,0.00003618209,0.00002072578,0.001512178],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002524832,"threshold_uncertainty_score":0.4483825,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01854449831199435,"score_gpt":0.2759412325114691,"score_spread":0.2573967341994747,"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."}}