{"id":"W2141317543","doi":"10.5006/c2008-08146","title":"Pipeline Corrosion Monitoring by Fiber Optic Distributed Strain and Temperature Sensors","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Fiber Optic Sensors","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; OZ Optics (Canada)","funders":"","keywords":"Corrosion; Optical fiber; Pipeline (software); Materials science; Fiber optic sensor; Strain (injury); Corrosion monitoring; Distributed acoustic sensing; Optoelectronics; Composite material; Fiber; Computer science; Engineering; Mechanical engineering; Telecommunications","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":[0.0001844255,0.0004123808,0.0002138892,0.0003040562,0.0001040989,0.0001824578,0.0003457975,0.0002491391,0.000337598],"category_scores_gemma":[0.0004397373,0.000211944,0.0001057944,0.0002188025,0.0002723727,0.0004078314,0.0002612498,0.0002321008,0.0001151024],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003693097,"about_ca_system_score_gemma":0.0002032409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001779576,"about_ca_topic_score_gemma":0.002691029,"domain_scores_codex":[0.9996133,0.00004377076,0.000007902649,0.0000776302,0.0002313858,0.00002604346],"domain_scores_gemma":[0.9997092,0.00003785706,0.0001019164,0.00001660211,0.0001159283,0.00001851626],"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":[0.0001404014,0.00004140991,0.006110604,0.00003186729,0.000009367671,0.00003695296,0.00004182163,0.003883977,0.9751626,0.00006827788,0.0001232085,0.0143494],"study_design_scores_gemma":[0.00003988701,0.0004705402,0.02981265,0.00000919287,0.00003458949,0.0003073682,0.00005881094,0.09385074,0.8743273,0.0001242053,0.0009244882,0.0000402109],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.966458,0.0002223382,0.03210463,0.0000762565,0.00001377299,0.00001135711,0.00009606805,0.0003026329,0.0007148911],"genre_scores_gemma":[0.9903641,0.00007647736,0.008857869,0.00001084806,0.000006369071,0.000005733085,0.00003672971,0.000007934915,0.0006339299],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001779576,"threshold_uncertainty_score":0.00353837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008632114328436712,"score_gpt":0.211646178250987,"score_spread":0.2030140639225503,"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."}}