{"id":"W33863569","doi":"10.1016/j.jemermed.2021.02.022","title":"Fiber Optic Sensors for Extreme Environments","year":2012,"lang":"en","type":"article","venue":"˜The œJournal of emergency medicine","topic":"Advanced Fiber Optic Sensors","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Memorial University of Newfoundland; University of Toronto","keywords":"Optical fiber; Materials science; Fiber optic sensor; Distributed acoustic sensing; Rayleigh scattering; Electronics; Fiber; Sensitivity (control systems); Optoelectronics; Computer science; Nanotechnology; Optics; Electronic engineering; Electrical engineering; Telecommunications; Engineering; Physics","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":[0.0003014352,0.0005632387,0.0001998217,0.0005282004,0.0003837461,0.0007056991,0.0004884844,0.001459119,0.005133286],"category_scores_gemma":[0.0007328269,0.0001505045,0.0002398821,0.0003090739,0.0004690606,0.001041132,0.0008301712,0.0008239056,0.002526621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002267431,"about_ca_system_score_gemma":0.000277753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002800734,"about_ca_topic_score_gemma":0.0004486073,"domain_scores_codex":[0.9996518,0.00005539301,0.00001685201,0.00003392293,0.000213883,0.00002815272],"domain_scores_gemma":[0.9995963,0.0001032911,0.00008469994,0.00005575036,0.0001236162,0.00003642065],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002624934,0.0001198178,0.009085024,0.000934188,0.00006376897,0.01087825,0.0004811905,0.002363482,0.286506,0.0229693,0.03807334,0.6282633],"study_design_scores_gemma":[0.00004076405,0.0006168206,0.01256516,0.0005604982,0.00008075809,0.07663198,0.0006848313,0.022962,0.146051,0.01968959,0.7199549,0.0001616702],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2184681,0.1337945,0.439981,0.02314615,0.01028487,0.0003645346,0.0005897242,0.006080418,0.1672906],"genre_scores_gemma":[0.8178362,0.022578,0.115823,0.003104625,0.001299965,0.00009908943,0.0002142654,0.000182006,0.03886287],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005133286,"threshold_uncertainty_score":0.01717252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04851892880966199,"score_gpt":0.281795099244024,"score_spread":0.233276170434362,"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."}}