{"id":"W2917334049","doi":"10.1016/j.bios.2019.02.017","title":"Development of an electrochemical impedimetric immunosensor for Corticotropin Releasing Hormone (CRH) using half-antibody fragments as elements of biorecognition","year":2019,"lang":"en","type":"article","venue":"Biosensors and Bioelectronics","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"World Anti-Doping Agency","keywords":"Detection limit; Dielectric spectroscopy; Cyclic voltammetry; Chemistry; Electrochemistry; Colloidal gold; Chromatography; Electrode; Nanoparticle; Analytical Chemistry (journal); Nuclear chemistry; Materials science; Nanotechnology","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":[0.00011492,0.0002601601,0.0003822546,0.0001956138,0.00009369668,0.00001645622,0.0001276861,0.0002494918,0.00000160229],"category_scores_gemma":[0.00006825836,0.0002365083,0.0001335602,0.0002868405,0.00009496731,0.00001234673,0.00006798117,0.00009758845,6.628046e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005189858,"about_ca_system_score_gemma":0.0001523593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000161988,"about_ca_topic_score_gemma":0.000004549026,"domain_scores_codex":[0.9981971,0.00003649014,0.0006390152,0.0004825209,0.0002137752,0.0004310799],"domain_scores_gemma":[0.9989111,0.00001760498,0.0004527615,0.000279863,0.0002610962,0.00007757375],"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":[0.0004796032,0.0001844743,0.0002794471,0.00005280917,0.0001678467,3.317264e-7,0.00002194725,6.710729e-7,0.9876288,0.00003147785,0.000003665577,0.01114888],"study_design_scores_gemma":[0.0008682724,0.001871113,0.0003876709,0.00004011521,0.00009111024,0.00001994555,0.0001213936,0.0009246608,0.9945613,0.00006954715,0.000741248,0.0003036011],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959435,0.001194053,0.002313796,0.000009786384,0.00003288956,0.0004466792,0.00002341698,0.00001917599,0.00001663688],"genre_scores_gemma":[0.9185537,0.001394609,0.07947013,0.00002867108,0.00004696313,0.000004223998,0.0004460171,0.00003137992,0.00002430229],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07738986,"threshold_uncertainty_score":0.964453,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01148602586859227,"score_gpt":0.3008011203093851,"score_spread":0.2893150944407928,"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."}}