{"id":"W2036448500","doi":"10.1021/ac049318q","title":"Label-Free Reading of Microarray-Based Immunoassays with Surface Plasmon Resonance Imaging","year":2004,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Advanced Biosensing Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":195,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Surface plasmon resonance; Chemistry; Microfluidics; Protein microarray; Substrate (aquarium); Nanotechnology; Antigen; Protein Array Analysis; DNA microarray; Biosensor; Surface plasmon; Plasmon; Optoelectronics; Materials science; Nanoparticle; 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":[0.00007550403,0.0001483128,0.0001486696,0.000008912095,0.00005941607,0.00001112731,0.0002438599,0.00009674955,0.00000550164],"category_scores_gemma":[0.0000581067,0.0001350372,0.00005792031,0.0001371911,0.000216092,0.000003228518,0.00007848352,0.0001163942,0.000001250551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003102784,"about_ca_system_score_gemma":0.00008942596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002035149,"about_ca_topic_score_gemma":0.000002622613,"domain_scores_codex":[0.9991437,0.000005802035,0.0001889674,0.0003285587,0.0001182074,0.0002147522],"domain_scores_gemma":[0.99909,0.00001318398,0.0000886259,0.0006378453,0.0001057912,0.00006452099],"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":[0.00006987047,0.00007301293,0.0006886455,0.00002525304,0.00001161317,0.000005082069,0.000002718632,0.0003336872,0.9980311,0.000204252,0.0003467891,0.0002080026],"study_design_scores_gemma":[0.0006952582,0.00004302833,0.00008747375,0.00007490423,0.00002285374,0.00001828253,0.00001729876,0.0004335369,0.9941521,0.0004131483,0.003861877,0.000180187],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9606059,0.0004362426,0.03388718,0.00093561,0.000007955643,0.0001106705,0.000051663,0.00005544561,0.003909288],"genre_scores_gemma":[0.955971,0.00002640044,0.04346853,0.0001257538,0.00003445052,0.000004002037,0.00008082687,0.00002294054,0.0002660772],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009581351,"threshold_uncertainty_score":0.5506659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006715402634781659,"score_gpt":0.2488777393678021,"score_spread":0.2421623367330204,"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."}}