{"id":"W1991665099","doi":"10.1021/la700701x","title":"Spectroscopically Encoded Microspheres for Antigen Biosensing","year":2007,"lang":"en","type":"article","venue":"Langmuir","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Institute for Nanotechnology; University of Alberta; Steacie Institute for Molecular Sciences; University of Ottawa","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institutes of Health; University of Alberta; University of Ottawa","keywords":"Polymerization; Bead; Immunoassay; Microsphere; Chemistry; Conjugated system; Dispersion polymerization; Antigen; Bioconjugation; Chromatography; Biosensor; Methacrylic acid; Nanotechnology; Combinatorial chemistry; Antibody; Materials science; Chemical engineering; Polymer; Biology; Organic chemistry; Immunology","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":[0.0001679954,0.0001150711,0.000121688,0.00002706703,0.00009748375,0.00001873219,0.00009045237,0.000122984,0.000001334214],"category_scores_gemma":[0.00004133637,0.00009827646,0.0001050962,0.00007827313,0.0000635676,0.000001742836,0.00003611443,0.00004247883,0.000002293166],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001010185,"about_ca_system_score_gemma":0.00001273135,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007211788,"about_ca_topic_score_gemma":0.0000939955,"domain_scores_codex":[0.9992465,0.00001009183,0.0001545546,0.0002582129,0.0000637691,0.0002668378],"domain_scores_gemma":[0.9996336,0.00001199322,0.00005798783,0.0001847856,0.00006933579,0.00004227384],"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":[0.00006511254,0.00002165427,0.001182463,0.00000633003,0.00002555258,0.000002930782,0.000009846506,2.156498e-7,0.9926625,0.00009743485,0.002057555,0.003868344],"study_design_scores_gemma":[0.000177144,0.0001087338,0.002724833,0.000006693566,0.00001098684,0.000009306762,0.00003429052,0.000008237661,0.9467027,0.0001512736,0.04992565,0.0001401294],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9341567,0.0002132732,0.0640227,0.0001612318,0.00005533119,0.0001370676,0.00001242551,0.00006456277,0.001176676],"genre_scores_gemma":[0.9269173,0.00003453371,0.07157372,0.0004050081,0.0003516304,0.000001498987,0.000095007,0.00001778889,0.0006035235],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04786809,"threshold_uncertainty_score":0.4007598,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00848907201145405,"score_gpt":0.2973065135107202,"score_spread":0.2888174414992661,"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."}}