{"id":"W4401521327","doi":"10.1002/admt.202400633","title":"AI‐Assisted Plasmonic Enhanced Colorimetric Fluidic Device for Hydrogen Peroxide Detection from Cancer Cells","year":2024,"lang":"en","type":"article","venue":"Advanced Materials Technologies","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Fonds de recherche du Québec – Nature et technologies; Canada Foundation for Innovation; Natural Sciences and Engineering Research Council of Canada; Université du Québec à Montréal; Consejo Nacional de Ciencia y Tecnología; Canada Research Chairs; McGill University","keywords":"Hydrogen peroxide; Plasmon; Fluidics; Nanotechnology; Cancer detection; Materials science; Optoelectronics; Chemistry; Cancer; Medicine; Engineering; Biochemistry; Electrical engineering; Internal medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000321355,0.0003924929,0.0002826974,0.0002780416,0.0002140291,0.0003475325,0.0007546336,0.000653571,0.0007328417],"category_scores_gemma":[0.0003313007,0.0002036647,0.0002049981,0.0001840034,0.0002423578,0.0003729462,0.0002974898,0.0004691071,0.0003842195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004270939,"about_ca_system_score_gemma":0.0002334016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000248103,"about_ca_topic_score_gemma":0.0003745743,"domain_scores_codex":[0.9998116,0.00002928944,0.00001348887,0.00005838593,0.00006766353,0.00001960767],"domain_scores_gemma":[0.9998658,0.00004641508,0.00002794543,0.00001236132,0.0000322934,0.00001527415],"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":[0.00002852687,0.0000288066,0.0000694583,0.00004565102,0.000003765828,0.00003965072,0.00002018501,0.0001977402,0.9956601,0.0002574936,0.0002814272,0.00336716],"study_design_scores_gemma":[0.000009538026,0.0001241453,0.0003386961,0.00000420759,0.000008751858,0.0001063627,0.000009641967,0.007151594,0.989534,0.00005967182,0.002635825,0.00001762322],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7401732,0.005918525,0.2422234,0.001338506,0.001114581,0.0002244513,0.0007852527,0.00314756,0.005074426],"genre_scores_gemma":[0.8688518,0.001320801,0.1226423,0.0005135285,0.0001101021,0.0002114295,0.0002450558,0.00003490492,0.006070145],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007546336,"threshold_uncertainty_score":0.003098845,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01008906395096859,"score_gpt":0.2879317495560343,"score_spread":0.2778426856050658,"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."}}