{"id":"W2528503471","doi":"10.1021/acs.analchem.6b02804","title":"Limits of Detection and Quantification of Electrochemical Quartz-Crystal Nanobalance in Platinum Electrochemistry and Electrocatalysis Research","year":2016,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Electrochemical Analysis and Applications","field":"Chemistry","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Queen's University; Canada Foundation for Innovation","keywords":"Chemistry; Electrochemistry; Detection limit; Electrocatalyst; Cyclic voltammetry; Platinum; Electrode; Electrolyte; Voltammetry; Analytical Chemistry (journal); Quartz; Supporting electrolyte; Crystal (programming language); Aqueous solution; Catalysis; Inorganic chemistry; Chromatography; Physical chemistry; Materials science; Organic chemistry; Metallurgy","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":[0.009169488,0.001593794,0.001099885,0.002592742,0.0008263888,0.002244326,0.003109181,0.005440387,0.001315613],"category_scores_gemma":[0.01745127,0.001506127,0.001048174,0.00166527,0.002264445,0.00201096,0.002415099,0.002191963,0.0009516082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002086133,"about_ca_system_score_gemma":0.001651256,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001739805,"about_ca_topic_score_gemma":0.002157932,"domain_scores_codex":[0.9791165,0.007323255,0.001335779,0.003649856,0.007918595,0.0006560147],"domain_scores_gemma":[0.991652,0.005459479,0.0007226226,0.000693063,0.001252935,0.0002198595],"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":[0.0001720213,0.0001575504,0.001350718,0.0005298525,0.00006377137,0.0001233736,0.0002281796,0.001014265,0.9731108,0.003641848,0.0006696432,0.01893802],"study_design_scores_gemma":[0.00003302156,0.0003800397,0.002205089,0.000089483,0.00005905228,0.0005417338,0.00009907133,0.01130315,0.9701579,0.002158463,0.01291244,0.00006050746],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1544367,0.02191106,0.8036512,0.001914844,0.001489916,0.001389564,0.001301762,0.001689994,0.01221498],"genre_scores_gemma":[0.4113953,0.007515301,0.5668576,0.001752135,0.000291424,0.003474102,0.001572619,0.0001714871,0.006970126],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009169488,"threshold_uncertainty_score":0.04849344,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01931941830685562,"score_gpt":0.2918526046578347,"score_spread":0.2725331863509791,"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."}}