{"id":"W2599552753","doi":"10.1021/acsami.6b15989","title":"Magnetic Printing of a Biosensor: Inexpensive Rapid Sensing To Detect Picomolar Amounts of Antigen with Antibody-Functionalized Carbon Nanotubes","year":2017,"lang":"en","type":"article","venue":"ACS Applied Materials & Interfaces","topic":"Microfluidic and Bio-sensing Technologies","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Biosensor; Materials science; Carbon nanotube; Nanotechnology; Magnetic nanoparticles; Current (fluid); Nanoparticle; Surface modification; Chemical engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001986924,0.0002900781,0.0005984303,0.0001664591,0.0001033464,0.00009985739,0.0003342798,0.0001322934,0.00002784295],"category_scores_gemma":[0.00007136768,0.0002390989,0.0000195728,0.0000796263,0.0002525682,0.00006052764,0.0002542298,0.00008486054,0.000007843543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002549183,"about_ca_system_score_gemma":0.00001674212,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002534828,"about_ca_topic_score_gemma":0.00001423969,"domain_scores_codex":[0.9987307,0.00002103789,0.0004746092,0.0002923643,0.0001824807,0.0002987896],"domain_scores_gemma":[0.9989238,0.00004126695,0.0002524061,0.0006305663,0.0001222691,0.00002969535],"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":[0.0001730576,0.000009283458,0.0001807637,0.0001824506,0.00008214002,0.000006481901,0.0002152079,0.00002904729,0.9938136,0.00004948112,0.00002963378,0.005228886],"study_design_scores_gemma":[0.0004248706,0.0001456622,0.001842755,0.0003186381,0.00003958078,0.00002004711,0.0002664779,0.000007363777,0.996451,0.00009180526,0.0001247261,0.0002670933],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976968,0.0004398655,0.0001431065,0.00003170964,0.0003128055,0.0003925124,0.00002896639,0.0002427857,0.0007114345],"genre_scores_gemma":[0.9948096,0.0002508097,0.004813696,0.00001132562,0.00004255643,0.000004439065,0.000005481323,0.00004827155,0.00001382945],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004961793,"threshold_uncertainty_score":0.975017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01066549364646815,"score_gpt":0.2254763136866128,"score_spread":0.2148108200401446,"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."}}