{"id":"W2104449171","doi":"10.1016/j.talanta.2010.11.010","title":"Ultrasonic frequency analysis of antibody-linked hydrogel biosensors for rapid point of care testing","year":2010,"lang":"en","type":"article","venue":"Talanta","topic":"Microfluidic and Capillary Electrophoresis Applications","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Biosensor; Analyte; Chemistry; Point of care; Opacity; Ultrasonic sensor; Chromatography; Polymer; Whole blood; Point-of-care testing; Biomedical engineering; Nanotechnology; Analytical Chemistry (journal); Acoustics; Optics; Materials science; Biochemistry","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":[],"consensus_categories":[],"category_scores_codex":[0.00007768295,0.0001145095,0.0003001529,0.000181374,0.00003588185,0.000004174196,0.000155122,0.00008196662,0.00007212799],"category_scores_gemma":[0.00004564656,0.0001122534,0.0001590644,0.0006551915,0.0000586268,0.00002558789,0.000009231916,0.000101461,0.00000258298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001416636,"about_ca_system_score_gemma":0.00002367712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005698152,"about_ca_topic_score_gemma":0.0000445812,"domain_scores_codex":[0.9992828,0.00000545607,0.0002998958,0.0001438315,0.00008492102,0.0001831056],"domain_scores_gemma":[0.9993297,0.000114138,0.00007827904,0.0003277628,0.0001072948,0.00004275295],"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":[0.00000312313,0.00001496988,0.003371755,0.0001035038,0.0002694681,3.387299e-7,0.0002065814,0.00004967691,0.9940807,0.0009984134,0.0004710662,0.0004304699],"study_design_scores_gemma":[0.000217837,0.00006755813,0.006443488,0.00001884718,0.000641837,0.000003851836,0.0001917386,0.003282199,0.9882968,0.0001719446,0.0004887255,0.0001751901],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937155,0.004504624,0.0003557878,0.000006519806,0.00004861117,0.0002000656,0.0002185215,0.0001031069,0.0008472264],"genre_scores_gemma":[0.9970914,0.002150492,0.0005006621,0.000004996494,0.00002822706,0.00001717701,0.0001718363,0.0000288453,0.00000641409],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005783851,"threshold_uncertainty_score":0.4577562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00826316252947617,"score_gpt":0.2323476383284963,"score_spread":0.2240844757990201,"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."}}