{"id":"W3009402132","doi":"10.3390/cryst10030186","title":"Improving Linear Range Limitation of Non-Enzymatic Glucose Sensor by OH− Concentration","year":2020,"lang":"en","type":"article","venue":"Crystals","topic":"Electrochemical sensors and biosensors","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Electrolyte; Linear relationship; Fourier transform infrared spectroscopy; Linear range; Range (aeronautics); Amperometry; Analytical Chemistry (journal); Chemistry; Materials science; Nuclear magnetic resonance; Chromatography; Electrode; Mathematics; Optics; Physics; Detection limit; Electrochemistry; Physical chemistry; 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":[0.002229967,0.001045702,0.0007413116,0.0005803655,0.0002919239,0.001232901,0.002218987,0.002043925,0.002338588],"category_scores_gemma":[0.002884325,0.0006461981,0.0005594671,0.0005157453,0.0005560075,0.001912159,0.001107343,0.001765941,0.002041131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004328341,"about_ca_system_score_gemma":0.0003127035,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003712357,"about_ca_topic_score_gemma":0.0005961154,"domain_scores_codex":[0.9974607,0.0003802243,0.0001716673,0.0006174469,0.001175749,0.0001941733],"domain_scores_gemma":[0.9972439,0.001493876,0.0002326207,0.0002087449,0.00074292,0.0000779981],"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":[0.00004350083,0.00002721182,0.0001477833,0.0001829036,0.00000737377,0.00005023382,0.00006871324,0.00006056259,0.9931617,0.0002167267,0.0001464245,0.005887063],"study_design_scores_gemma":[0.000005765943,0.0001021067,0.0003715061,0.00001894128,0.00001620704,0.0001544515,0.00004216011,0.001326489,0.9943339,0.0001619964,0.003451925,0.00001451603],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4781586,0.03941818,0.4586085,0.003600999,0.001401182,0.0003887053,0.000489994,0.003214343,0.01471934],"genre_scores_gemma":[0.8075121,0.01201853,0.1636019,0.002953884,0.000340663,0.0005195872,0.0006560116,0.0003906238,0.01200671],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002338588,"threshold_uncertainty_score":0.01179338,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009070801009716275,"score_gpt":0.2000382012202014,"score_spread":0.1909674002104852,"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."}}