{"id":"W2971274402","doi":"10.3389/fchem.2019.00617","title":"Affinity-Based Detection of Biomolecules Using Photo-Electrochemical Readout","year":2019,"lang":"en","type":"review","venue":"Frontiers in Chemistry","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biosensor; Transduction (biophysics); Nanotechnology; Biomolecule; SIGNAL (programming language); Analyte; Materials science; Computer science; Chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001725172,0.0004540286,0.001206537,0.0001402111,0.00002971018,0.00001360582,0.0003375393,0.001024613,0.000001808873],"category_scores_gemma":[0.0001133577,0.0004319003,0.0006008834,0.0003934039,0.0001673272,0.00000255743,0.00009257079,0.0003733751,6.09979e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001480482,"about_ca_system_score_gemma":0.0003196042,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006412842,"about_ca_topic_score_gemma":0.000001437943,"domain_scores_codex":[0.9981068,0.0000737622,0.000611998,0.000699851,0.000178571,0.0003290086],"domain_scores_gemma":[0.9986456,0.00001631089,0.0005217832,0.0006746801,0.00008115576,0.00006049071],"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":[0.00004280686,0.0000715448,0.00001538259,0.005692636,0.0001412437,0.000003980109,0.000001096698,0.000001721985,0.8944413,6.587741e-8,0.0001350745,0.09945316],"study_design_scores_gemma":[0.0001554713,0.00003615419,1.098827e-7,0.001758718,0.0003341439,0.00001844139,0.000007902233,0.00007986869,0.8173236,0.000006926742,0.1798988,0.0003797899],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001781206,0.9798491,0.01761319,0.000001887903,0.0001361021,0.0003029747,0.0000632886,0.00003292102,0.0002193172],"genre_scores_gemma":[0.00709388,0.9695524,0.02209687,0.00001933371,0.0001792962,0.00002162303,0.000803658,0.00008603022,0.0001469332],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.1797637,"threshold_uncertainty_score":0.9998133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02293452513768826,"score_gpt":0.3129013785909077,"score_spread":0.2899668534532194,"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."}}