{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003321069,0.0002116561,0.000183363,0.00003767005,0.00009272954,0.00001953595,0.00006186395,0.0001324771,0.00008547935],"category_scores_gemma":[0.00003143511,0.0001973175,0.00002868017,0.0001561423,0.00005131508,0.0001351202,0.00002127929,0.0002438002,0.00004306969],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005316318,"about_ca_system_score_gemma":0.000004587496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000323101,"about_ca_topic_score_gemma":3.014682e-7,"domain_scores_codex":[0.9991542,0.00001009273,0.0001939792,0.0002092342,0.0001445259,0.0002879663],"domain_scores_gemma":[0.9995619,0.00006495061,0.00001656813,0.000186426,0.00003443572,0.0001357021],"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":[0.00002916551,0.00005586134,0.001748451,0.00009911921,0.00003654587,0.0002366108,0.0006885853,0.1872381,0.7565311,0.00005855064,0.05033496,0.002942977],"study_design_scores_gemma":[0.004890634,0.0002311692,0.01979019,0.0003340362,0.0001175459,0.001986884,0.002169795,0.2531581,0.6728284,0.0001187151,0.04080038,0.003574087],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995878,0.0004450601,0.001725881,0.00005411051,0.0002182814,0.0001326413,0.0001316602,0.000539122,0.0008751991],"genre_scores_gemma":[0.9819126,0.0002100581,0.01227994,0.000009930764,0.0001205787,0.000005866694,0.00009166357,0.00005681549,0.005312627],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08370265,"threshold_uncertainty_score":0.8046374,"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."}}