{"id":"W4200016088","doi":"10.1109/embc46164.2021.9630056","title":"Optimization &amp; Characterization of Interdigitated Electrodes for Microbial Growth Monitoring","year":2021,"lang":"en","type":"article","venue":"2021 43rd Annual International Conference of the IEEE Engineering in Medicine &amp; Biology Society (EMBC)","topic":"Microbial Fuel Cells and Bioremediation","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Université Laval","keywords":"Microscale chemistry; Microelectrode; Electrode; Electrical impedance; Characterization (materials science); Dielectric spectroscopy","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":[0.0006469921,0.0007167701,0.0003419917,0.0003306372,0.0001378045,0.0005411178,0.0008883088,0.0005961895,0.0004855069],"category_scores_gemma":[0.0009863009,0.0002342247,0.0002633086,0.000359596,0.0001692343,0.0005552642,0.0002763734,0.0003427572,0.0004201525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002982128,"about_ca_system_score_gemma":0.000251913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002875447,"about_ca_topic_score_gemma":0.0008017966,"domain_scores_codex":[0.999488,0.00006627692,0.00004920963,0.0001265971,0.0002314187,0.000038496],"domain_scores_gemma":[0.9995415,0.00009027908,0.00008981363,0.00006004021,0.0002000901,0.00001825122],"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":[0.00003473154,0.00003297961,0.0005009857,0.0001021903,0.000008983483,0.00006163531,0.00001774893,0.0006664623,0.9868946,0.0001364294,0.00008765374,0.01145569],"study_design_scores_gemma":[0.000003724746,0.0001094855,0.001164344,0.000003054543,0.000008589385,0.00005886188,0.0000163538,0.003832962,0.9930098,0.00003638083,0.001751327,0.000005053731],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7219406,0.003930899,0.2665415,0.0005245983,0.0002323965,0.0004186414,0.0009952973,0.0006811395,0.004735021],"genre_scores_gemma":[0.8078974,0.001290193,0.1864591,0.000126173,0.00003302186,0.0002310319,0.0006633668,0.00006915025,0.003230601],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008883088,"threshold_uncertainty_score":0.003421664,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02202029471972499,"score_gpt":0.2597999149252807,"score_spread":0.2377796202055557,"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."}}