{"id":"W3089800399","doi":"10.1149/1945-7111/abbdd6","title":"Salicylate Method for Ammonia Quantification in Nitrogen Electroreduction Experiments: The Correction of Iron III Interference","year":2020,"lang":"en","type":"article","venue":"Journal of The Electrochemical Society","topic":"Ammonia Synthesis and Nitrogen Reduction","field":"Chemical Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"European Social Fund; Division of Materials Research; Natural Sciences and Engineering Research Council of Canada; Materials Research Science and Engineering Center, Harvard University; Helmholtz-Zentrum Dresden-Rossendorf; Toyota Research Institute; Generalitat Valenciana; National Science Foundation","keywords":"Calibration curve; Interference (communication); Ammonia; Chemistry; Calibration; Sodium salicylate; Analytical Chemistry (journal); Nitrogen; Detection limit; Chromatography; Mathematics; Computer science; Statistics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004399419,0.0001395251,0.0002769035,0.00001896764,0.00007331108,0.00001487389,0.0003437799,0.0001263525,0.000007778214],"category_scores_gemma":[0.0002736159,0.00008780038,0.0004657066,0.0003448392,0.0000524594,0.0001092301,0.00003382441,0.0005012159,5.516558e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002471643,"about_ca_system_score_gemma":0.00005675471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001899486,"about_ca_topic_score_gemma":0.000001080479,"domain_scores_codex":[0.9987267,0.000079071,0.0005847345,0.0001611667,0.0002262642,0.000222073],"domain_scores_gemma":[0.9989597,0.0001680057,0.0005286086,0.0001389205,0.0001501735,0.00005464798],"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":[0.0003378949,0.00006179197,0.00006778,0.00002191742,0.00008366925,3.757535e-8,0.001078559,0.0002006062,0.9955316,0.0001035272,0.0004692261,0.002043415],"study_design_scores_gemma":[0.0003995126,0.0001035884,0.00003246822,0.00003707871,0.0000757575,0.00002049213,0.0006060021,0.04830536,0.9497478,0.000311531,0.000277222,0.00008320314],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6466467,0.0006122565,0.3493122,0.00284745,0.0002846223,0.0002623521,0.000001370564,0.00001711703,0.0000159528],"genre_scores_gemma":[0.9877765,0.00007307358,0.01160942,0.0001130106,0.0003618544,0.00002072143,0.000002247079,0.00002052448,0.00002264245],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3411298,"threshold_uncertainty_score":0.3580396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0210795974547055,"score_gpt":0.2807234315526196,"score_spread":0.2596438340979141,"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."}}