{"id":"W1996504005","doi":"10.1115/caneus2006-11028","title":"Micro Fiber Optical Sensor Interrogation Systems for Aerospace Applications","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Fiber Optic Sensors","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada; National Research Council Canada","funders":"","keywords":"Interrogation; Fiber Bragg grating; Multiplexing; Materials science; Microsystem; Aerospace; Fiber optic sensor; Optical fiber; Demultiplexer; Waveguide; Electronic engineering; Computer science; Optics; Optoelectronics; Engineering; Nanotechnology; Aerospace engineering; Telecommunications; Physics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002899261,0.0002956948,0.0002063625,0.000357213,0.0002618029,0.0005141125,0.0003594128,0.0004529808,0.004376353],"category_scores_gemma":[0.0004533598,0.000182523,0.0001147265,0.0002895413,0.0002062669,0.000712741,0.0002671423,0.0004081778,0.00152498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003419216,"about_ca_system_score_gemma":0.0003496315,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003598304,"about_ca_topic_score_gemma":0.0009017817,"domain_scores_codex":[0.9996537,0.000045842,0.00001463656,0.00004937029,0.0002157584,0.000020573],"domain_scores_gemma":[0.999768,0.00005787481,0.00004487334,0.00003094632,0.00008286311,0.00001547885],"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":[0.0001166959,0.00004721698,0.000722351,0.0002251413,0.00001589033,0.00008206494,0.00007976066,0.0009046315,0.7674519,0.006930015,0.008119895,0.2153043],"study_design_scores_gemma":[0.00002797106,0.000507729,0.003452302,0.00004770487,0.00004063188,0.0006775862,0.00006833407,0.03500123,0.7614077,0.00323213,0.1954855,0.00005103451],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.145492,0.03266582,0.7625482,0.003833912,0.00143103,0.0005087128,0.001189832,0.009352059,0.0429785],"genre_scores_gemma":[0.4732281,0.007037045,0.4831314,0.0009122002,0.0004300027,0.0002378741,0.0005499002,0.0001592907,0.03431424],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004376353,"threshold_uncertainty_score":0.01464033,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008271027519509661,"score_gpt":0.2254718249807043,"score_spread":0.2172007974611946,"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."}}