{"id":"W1969472517","doi":"10.1039/c5ra05854f","title":"Highly manufacturable graphene oxide biosensor for sensitive Interleukin-6 detection","year":2015,"lang":"en","type":"article","venue":"RSC Advances","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal College of Physicians and Surgeons of Canada","funders":"National Institutes of Health; Loughborough University; National Health Research Institutes; National Institute for Health and Care Research; University Hospitals of Leicester NHS Trust","keywords":"Graphene; Oxide; Biosensor; Nanotechnology; Materials science; Chemical vapor deposition; Transducer; Optoelectronics; Chemistry; Electrical engineering; Engineering","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":[0.000270935,0.0004981186,0.0002632406,0.0003830131,0.0001897648,0.000314035,0.0008080755,0.0007086114,0.001136928],"category_scores_gemma":[0.0004656281,0.0002979982,0.0002165459,0.0002865053,0.0001898173,0.0003880805,0.000280623,0.0005108081,0.00103143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003398609,"about_ca_system_score_gemma":0.000189631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000447508,"about_ca_topic_score_gemma":0.001573865,"domain_scores_codex":[0.9995565,0.00004385928,0.00002833546,0.00007835468,0.0002558674,0.00003706236],"domain_scores_gemma":[0.9997899,0.00004173821,0.00004442501,0.00004236946,0.00005933079,0.00002216729],"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":[0.00001394333,0.000008600918,0.00007664907,0.0000214077,0.000002514055,0.00004172571,0.000008231675,0.0001380245,0.9967651,0.0001115401,0.0002286702,0.002583551],"study_design_scores_gemma":[0.00000759145,0.0001416789,0.001745736,0.00000555091,0.00001130868,0.0001432689,0.00001256744,0.005962608,0.9865111,0.0001010985,0.005334984,0.0000224634],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7884994,0.003048397,0.1895137,0.001287638,0.0009150141,0.0002420346,0.002577695,0.003797152,0.01011887],"genre_scores_gemma":[0.7990025,0.0007854527,0.1897851,0.0002626462,0.00009749453,0.0001645475,0.001645938,0.0001162782,0.008140071],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001136928,"threshold_uncertainty_score":0.003803432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01297928177219026,"score_gpt":0.2751398613790046,"score_spread":0.2621605796068144,"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."}}