{"id":"W2807832819","doi":"10.1021/acs.chemmater.8b01324","title":"Accurate Coulometric Quantification of Hydrogen Absorption in Palladium Nanoparticles and Thin Films","year":2018,"lang":"en","type":"article","venue":"Chemistry of Materials","topic":"Electrocatalysts for Energy Conversion","field":"Energy","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canada First Research Excellence Fund; Canada Research Chairs; Canadian Institute for Advanced Research; Canada Foundation for Innovation; Google","keywords":"Palladium; Materials science; Hydrogen; Electrochemistry; Nanoparticle; Thin film; Coulometry; Chemical engineering; Analytical Chemistry (journal); Nanotechnology; Electrode; Chemistry; Catalysis; Organic chemistry; Physical chemistry","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":[0.0006585217,0.0005908954,0.0003924686,0.0007550601,0.0003137884,0.0007026567,0.0009805262,0.000610218,0.0006641634],"category_scores_gemma":[0.001258387,0.0003312613,0.000167689,0.0003420232,0.0004805571,0.0007302521,0.0004327905,0.001085187,0.0003502033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004131832,"about_ca_system_score_gemma":0.0003470418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006458733,"about_ca_topic_score_gemma":0.001768573,"domain_scores_codex":[0.9991288,0.0001102962,0.00005280475,0.0002330286,0.0004278378,0.00004735157],"domain_scores_gemma":[0.999387,0.0002625176,0.00008137962,0.00008939567,0.0001495061,0.00003009814],"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":[0.0000266757,0.00002596317,0.0002691035,0.00006725984,0.0000127138,0.00002766701,0.000022676,0.000147142,0.9906719,0.000292874,0.0001050546,0.008330999],"study_design_scores_gemma":[0.00000256188,0.00004788407,0.0002539048,0.000002392458,0.000005361097,0.00004532168,0.00001061251,0.001716838,0.9969636,0.00008118901,0.000865283,0.00000509025],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.447057,0.006346647,0.5364727,0.0005224935,0.0005437561,0.0003327105,0.001509982,0.002019073,0.005195584],"genre_scores_gemma":[0.6879277,0.002908569,0.3037366,0.0002700266,0.0000899703,0.0002281746,0.0007111856,0.0001205535,0.004007222],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0009805262,"threshold_uncertainty_score":0.00348264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01614086253190037,"score_gpt":0.2431351694195635,"score_spread":0.2269943068876631,"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."}}