{"id":"W4408828653","doi":"10.70477/nhug4798","title":"\"HIGHLY SENSITIVE, MULTIPLEXED DETECTION OF CIRCULATING BIOMARKERS USING A GOLD-NANOPARTICLE-EMBEDDED MEMBRANE\"","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Colloidal gold; Nanoparticle; Multiplexing; Membrane; Nanotechnology; Computer science; Materials science; Chemistry; Telecommunications; Biochemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007020356,0.0005560711,0.0004884874,0.0004636467,0.0003614812,0.0005416573,0.0009079198,0.001469863,0.0007155454],"category_scores_gemma":[0.0006531105,0.0005034292,0.0003252038,0.0002592952,0.0003491129,0.0005432705,0.0006411246,0.0006646386,0.0007624228],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004329987,"about_ca_system_score_gemma":0.0004031117,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003954915,"about_ca_topic_score_gemma":0.0009180173,"domain_scores_codex":[0.99942,0.00008500769,0.00002726067,0.0001912476,0.0001968362,0.00007955753],"domain_scores_gemma":[0.9998099,0.00004468919,0.00004016115,0.00001718612,0.00004911743,0.00003895044],"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":[0.0001742465,0.00002860734,0.0001879791,0.00008014815,0.0000122938,0.00008824119,0.00003473184,0.00007273989,0.9917177,0.0003403555,0.00069102,0.006571853],"study_design_scores_gemma":[0.000007766968,0.0000719443,0.0003399948,0.000002488016,0.00000727826,0.0001810837,0.000006056165,0.00141315,0.9963325,0.00003293725,0.001596303,0.00000855979],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6999932,0.009104503,0.2725317,0.003164354,0.001520165,0.0005334764,0.001628576,0.004587406,0.006936593],"genre_scores_gemma":[0.8190356,0.002467792,0.1565774,0.001309402,0.0002002589,0.0003253289,0.0008268621,0.00007476116,0.01918259],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001469863,"threshold_uncertainty_score":0.003712773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01430342890711203,"score_gpt":0.2800587539978472,"score_spread":0.2657553250907352,"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."}}