{"id":"W18072767","doi":"10.5162/imcs2012/2.2.6","title":"2.2.6 Developing Electrochemical Impedance Immunosensor for the Detection of Myoglobin","year":2012,"lang":"en","type":"article","venue":"Proceedings IMCS 2012","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Alberta Innovates; Department of Mechanical Engineering, University of Alberta; University of Alberta","keywords":"Myoglobin; Dielectric spectroscopy; Electrical impedance; Electrode; Reagent; Materials science; Electrochemistry; Microelectrode; Analytical Chemistry (journal); Chemistry; Chromatography; Biochemistry; Electrical engineering","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":[0.0006105475,0.000627664,0.0004892913,0.0004954254,0.0002033279,0.000497077,0.000612676,0.0008893548,0.0008534615],"category_scores_gemma":[0.0005648271,0.0003905037,0.0004520861,0.0004633574,0.0001901783,0.0005227739,0.0003114031,0.0006129082,0.0006627325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001723356,"about_ca_system_score_gemma":0.000223865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000173194,"about_ca_topic_score_gemma":0.0003324442,"domain_scores_codex":[0.9993805,0.0001109647,0.00005318573,0.0001352832,0.0002717771,0.0000484111],"domain_scores_gemma":[0.9998171,0.00003752754,0.00002181666,0.0000124432,0.00009981277,0.00001142809],"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":[0.00003130055,0.00001907536,0.0002113379,0.0001445842,0.000008307365,0.00007167453,0.00004802574,0.0001274936,0.9905558,0.0001850143,0.00008050203,0.00851699],"study_design_scores_gemma":[0.000004896787,0.0001146508,0.0009185282,0.00000973019,0.00001679271,0.0002869789,0.00002739522,0.002625558,0.9926802,0.00006178903,0.003243524,0.00001001319],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3938364,0.009438132,0.5829846,0.0006059557,0.0007339767,0.0005673988,0.0003550398,0.001458772,0.01001965],"genre_scores_gemma":[0.5625181,0.007014016,0.4130342,0.0003424834,0.0001100781,0.0005457883,0.0005670621,0.00008995753,0.01577833],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0008893548,"threshold_uncertainty_score":0.003228903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01369479232617246,"score_gpt":0.2819235753029642,"score_spread":0.2682287829767917,"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."}}