{"id":"W3094542389","doi":"10.1021/acsnano.0c03625","title":"Hexagonal Boron Nitride for Sulfur Corrosion Inhibition","year":2020,"lang":"en","type":"article","venue":"ACS Nano","topic":"MXene and MAX Phase Materials","field":"Materials Science","cited_by":96,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Division of Chemical, Bioengineering, Environmental, and Transport Systems; UT-Battelle; National Aeronautics and Space Administration","keywords":"Corrosion; Sulfur; Materials science; Sulfide; Coating; Hexagonal boron nitride; Boron; Metallurgy; Copper; Chemical engineering; Biofilm; Nanotechnology; Inorganic chemistry; Chemistry; Bacteria; Organic chemistry; Geology","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":[0.000196852,0.0001155214,0.0001789591,0.00002415744,0.0001113379,0.00008439929,0.0001134189,0.00006425783,0.0006724462],"category_scores_gemma":[0.0001422357,0.0001025938,0.00004685138,0.00007933535,0.00002886255,0.0001986641,0.00006957096,0.00002797808,0.0004861135],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002130473,"about_ca_system_score_gemma":0.00005262982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003536334,"about_ca_topic_score_gemma":0.000003698946,"domain_scores_codex":[0.9990575,0.00003797441,0.0002380006,0.0002714491,0.0001600649,0.0002350255],"domain_scores_gemma":[0.9995515,0.00005243845,0.0000901548,0.0001320173,0.0000701912,0.0001036582],"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":[0.000166152,0.00002528566,0.00002185784,0.00004588658,8.81234e-7,0.000003539106,0.0001169381,0.00000465991,0.9780894,0.0006006397,0.02071336,0.0002113967],"study_design_scores_gemma":[0.0006661654,0.0001850759,0.00002860464,0.00001853624,0.00001311528,0.000003696161,0.00003230382,0.00001631557,0.9591367,0.0005809619,0.03919031,0.0001281894],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994516,0.00004880951,0.002513044,0.001452197,0.0005550794,0.0003242703,0.0001860101,0.0001168418,0.0002877128],"genre_scores_gemma":[0.9955398,0.00001177456,0.001100671,0.002512945,0.0004904348,0.00005405498,0.0001038487,0.0000184749,0.0001680235],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01895268,"threshold_uncertainty_score":0.7362815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03282337536843872,"score_gpt":0.2623035545255077,"score_spread":0.229480179157069,"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."}}