{"id":"W2071821630","doi":"10.1016/j.apsusc.2013.06.168","title":"Characterization of anodized titanium for hydrometallurgical applications—Evidence for the reduction of cupric on titanium dioxide","year":2013,"lang":"en","type":"article","venue":"Applied Surface Science","topic":"Corrosion Behavior and Inhibition","field":"Materials Science","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; University of British Columbia","keywords":"Sulfuric acid; X-ray photoelectron spectroscopy; Titanium; Corrosion; Anodizing; Materials science; Titanium dioxide; Dielectric spectroscopy; Copper; Scanning electron microscope; Electrochemistry; Oxide; Metallurgy; Leaching (pedology); Inorganic chemistry; Nuclear chemistry; Chemistry; Chemical engineering; Electrode; Composite material","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002356558,0.0003263477,0.0002482303,0.0004316618,0.0003286143,0.0004255891,0.0006430988,0.0004593534,0.000961839],"category_scores_gemma":[0.0004663586,0.0001891813,0.00026034,0.0003083854,0.0002856337,0.0001684923,0.0001459255,0.0002553969,0.0002634457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003728315,"about_ca_system_score_gemma":0.0003137184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00402827,"about_ca_topic_score_gemma":0.005861828,"domain_scores_codex":[0.9997461,0.00002143792,0.00001183996,0.00003707448,0.0001372128,0.00004632224],"domain_scores_gemma":[0.9997393,0.00004471468,0.00002981778,0.00003719336,0.0001274498,0.00002157039],"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":[0.00005942963,0.00001025858,0.0001594158,0.00002651394,0.00000434788,0.00003152812,0.00002150218,0.00005122065,0.9988174,0.00002851261,0.00003183488,0.0007579786],"study_design_scores_gemma":[0.000003069411,0.00007576581,0.002249798,0.000001124473,0.000008434455,0.00003706668,0.00002685295,0.000791399,0.9961851,0.000008161516,0.0006092989,0.00000381233],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.993064,0.0005406988,0.003434661,0.00005057409,0.00002365484,0.00003248666,0.0002466258,0.0000549926,0.002552208],"genre_scores_gemma":[0.993605,0.0002814436,0.002692731,0.00003030838,0.000009821614,0.00002452094,0.0004762054,0.00003264369,0.002847339],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00402827,"threshold_uncertainty_score":0.008009613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03729569595910742,"score_gpt":0.2900035995394323,"score_spread":0.2527079035803249,"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."}}