{"id":"W2804863272","doi":"10.1117/12.2303621","title":"Fiber optic sensors for harsh environment sensing: case studies on environmental sensing","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Fiber Optic Sensors","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Optech (Canada)","funders":"","keywords":"Software deployment; Fiber optic sensor; Optical fiber; Electromagnetic interference; Computer science; Electro-optical sensor; Interference (communication); Remote sensing; Environmental monitoring; Environmental science; Electronic engineering; Engineering; Telecommunications; Geology","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":[0.002814336,0.000749699,0.0004930924,0.001439688,0.001574578,0.001666252,0.0009113195,0.00335544,0.0009980624],"category_scores_gemma":[0.002837918,0.0002313458,0.000569711,0.002297528,0.001382843,0.002119694,0.001288462,0.001025102,0.0004013595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007431021,"about_ca_system_score_gemma":0.0005238955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003847912,"about_ca_topic_score_gemma":0.009361111,"domain_scores_codex":[0.9969655,0.001188892,0.0001035022,0.0001992741,0.001313538,0.000229326],"domain_scores_gemma":[0.9971865,0.001672068,0.0002182879,0.0001942958,0.0006236873,0.0001051934],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006378926,0.001549389,0.04992336,0.004310734,0.0002236995,0.03032522,0.0130906,0.03126927,0.07214556,0.04981085,0.01982858,0.7268848],"study_design_scores_gemma":[0.00005949788,0.003964434,0.03466557,0.001812462,0.0002715143,0.03617755,0.01741698,0.02661192,0.1480173,0.01412895,0.7165491,0.0003247129],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6475345,0.1223124,0.08450136,0.009920925,0.0006867801,0.0007799728,0.0003053325,0.0002880618,0.1336706],"genre_scores_gemma":[0.8004273,0.0869009,0.09162399,0.001353307,0.0003462011,0.0001316557,0.000118053,0.00008601575,0.01901262],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003847912,"threshold_uncertainty_score":0.01488382,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02264211193444701,"score_gpt":0.2470712110223992,"score_spread":0.2244290990879521,"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."}}