{"id":"W2159861516","doi":"10.1002/anie.201200997","title":"Significantly Improved Analytical Sensitivity of Lateral Flow Immunoassays by Using Thermal Contrast","year":2012,"lang":"en","type":"article","venue":"Angewandte Chemie International Edition","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":213,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Division of Chemical, Bioengineering, Environmental, and Transport Systems; National Institute of Allergy and Infectious Diseases; University of Minnesota; McKnight Foundation; National Institutes of Health; National Science Foundation","keywords":"Sensitivity (control systems); Materials science; Contrast (vision); Thermal; Nanoparticle; Colloidal gold; Flow (mathematics); Nanotechnology; Biomedical engineering; Optics; Medicine; Mathematics; Electronic 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002281577,0.0001262345,0.0001501732,0.00005251285,0.00002983846,0.00002754959,0.00006128245,0.0001144032,0.0001682827],"category_scores_gemma":[0.00004157561,0.0001219136,0.00009514017,0.00007514574,0.00005373103,0.0003025082,0.00001807934,0.0001512295,0.000008287528],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000105263,"about_ca_system_score_gemma":0.000005791463,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004822882,"about_ca_topic_score_gemma":0.000002208571,"domain_scores_codex":[0.9992201,0.00001940984,0.0002264864,0.0001055664,0.0002191187,0.0002093535],"domain_scores_gemma":[0.9996382,0.00006237701,0.00004823707,0.00007846674,0.00009490821,0.00007781877],"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":[0.00002652659,0.00006293166,0.0007418561,0.0000147101,0.0000978542,0.00000127356,0.00003681557,0.0003355977,0.9968098,0.00002822123,0.0009431032,0.0009012717],"study_design_scores_gemma":[0.0002292853,0.00001066271,0.001889165,0.00001924711,0.00003022172,0.000009300879,0.00001441557,0.2286021,0.7687386,0.00001710823,0.0003281438,0.00011172],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.960915,0.00007047899,0.03552596,0.00008371552,0.001328212,0.00007772057,0.0002895172,0.00009803005,0.001611374],"genre_scores_gemma":[0.9985397,0.00001528475,0.0001919128,0.00003498284,0.0009814128,0.000002865963,0.0001643943,0.00001795506,0.00005146345],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2282665,"threshold_uncertainty_score":0.4971491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01158615448838463,"score_gpt":0.2271916483020786,"score_spread":0.215605493813694,"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."}}