{"id":"W2266407528","doi":"10.1149/ma2013-01/45/1489","title":"Miniaturized Electrochemical Immunosensor for Label-Free Detection of Growth Hormone","year":2013,"lang":"en","type":"article","venue":"ECS Meeting Abstracts","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"","keywords":"Growth hormone; Nanotechnology; Electrochemistry; Chemistry; Computer science; Chromatography; Combinatorial chemistry; Materials science; Hormone; Electrode; Biochemistry","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0004048312,0.0006541275,0.0004246913,0.0002907307,0.000215813,0.0004380406,0.001037776,0.0008838333,0.002750962],"category_scores_gemma":[0.0004445346,0.0003084266,0.0002712229,0.0001801126,0.0002137929,0.0003723655,0.0004103348,0.0007975652,0.001150817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004480112,"about_ca_system_score_gemma":0.0002514173,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003623703,"about_ca_topic_score_gemma":0.001164514,"domain_scores_codex":[0.999487,0.00007270554,0.00002201185,0.0001107729,0.0002603569,0.00004707821],"domain_scores_gemma":[0.9998282,0.00005516469,0.00001438873,0.00001964041,0.00005503758,0.00002750941],"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":[0.00005855459,0.00002509222,0.00003944181,0.00006129222,0.00000939891,0.00003240307,0.000005931834,0.00005344162,0.9942053,0.00008139561,0.0004049641,0.005022787],"study_design_scores_gemma":[0.00003036606,0.0002760916,0.0008815372,0.000008312427,0.00002880677,0.0001950031,0.00001196526,0.002234952,0.9858896,0.00006383392,0.01036658,0.00001303617],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6157494,0.02697398,0.3225321,0.002874305,0.004700829,0.001546073,0.004252567,0.004542169,0.0168287],"genre_scores_gemma":[0.7581516,0.005292773,0.2100955,0.001192825,0.0003871943,0.0006636757,0.00249864,0.0001396503,0.02157805],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.002750962,"threshold_uncertainty_score":0.009202898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006997633455416338,"score_gpt":0.2387066226519162,"score_spread":0.2317089891964998,"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."}}