{"id":"W2055814940","doi":"10.1109/sopo.2010.5504427","title":"Optical Biosensing with Spectroscopic Techniques","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Fiber Optic Sensors","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biosensor; Reflectometry; Refractive index; Materials science; Measure (data warehouse); Sensitivity (control systems); Optical sensing; Nanotechnology; Optoelectronics; Computer science; Electronic engineering; Engineering","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":[0.001124579,0.001125691,0.0007561838,0.001015225,0.0003609262,0.001148696,0.001168477,0.001352729,0.001864131],"category_scores_gemma":[0.001718234,0.0005447421,0.0005966279,0.000992285,0.0009411487,0.001812061,0.001412133,0.001531089,0.001827962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005246099,"about_ca_system_score_gemma":0.000385281,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001938228,"about_ca_topic_score_gemma":0.0001985667,"domain_scores_codex":[0.9982151,0.0003861376,0.00007306774,0.0002840811,0.0009314325,0.0001102879],"domain_scores_gemma":[0.9993824,0.0002875314,0.0001008981,0.00008341801,0.0001221628,0.00002362449],"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":[0.0000670314,0.00007809242,0.0001235088,0.0007345947,0.00003081473,0.0001173454,0.00007876475,0.0005505275,0.9357946,0.01152829,0.001107975,0.04978851],"study_design_scores_gemma":[0.00002142558,0.0002514374,0.0002370844,0.00005460935,0.0000256701,0.0005430795,0.00004459054,0.006249703,0.954328,0.003706239,0.03449738,0.00004083764],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06332561,0.03539773,0.8672192,0.001726358,0.0009267515,0.0005895677,0.0002353572,0.002021066,0.02855835],"genre_scores_gemma":[0.3292049,0.03393067,0.6215981,0.001713189,0.0007317977,0.0007538698,0.0002250009,0.0001903318,0.01165216],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001864131,"threshold_uncertainty_score":0.006236136,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004234508717461164,"score_gpt":0.2117863757847956,"score_spread":0.2075518670673344,"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."}}