{"id":"W2057318704","doi":"10.2118/173440-ms","title":"Cloud-Based Solution for Permanent Fiber-Optic DAS Flow Monitoring","year":2015,"lang":"en","type":"article","venue":"SPE Digital Energy Conference and Exhibition","topic":"Advanced Fiber Optic Sensors","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"Shell (Canada)","funders":"Shell Canada","keywords":"Computer science; Optical fiber; Cloud computing; Telecommunications; Operating system","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003531419,0.0006547674,0.0007405751,0.0006372155,0.0009113455,0.001057864,0.00162781,0.0007360335,0.004648134],"category_scores_gemma":[0.0005418579,0.0001863115,0.0003797802,0.0007351002,0.0002043276,0.001190687,0.001045117,0.0005734679,0.001052479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006855914,"about_ca_system_score_gemma":0.001200263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006556841,"about_ca_topic_score_gemma":0.008221334,"domain_scores_codex":[0.999551,0.00004817194,0.00002304975,0.0001057683,0.0001432118,0.0001287665],"domain_scores_gemma":[0.9995093,0.00005931991,0.00005486231,0.0001053101,0.0001852096,0.00008604794],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.004140621,0.002367382,0.01420706,0.0005288377,0.0003752754,0.001520549,0.0003894298,0.08945675,0.1624344,0.01827171,0.08359687,0.6227112],"study_design_scores_gemma":[0.0001355576,0.0002369366,0.002759183,0.00002599939,0.00006061711,0.000244252,0.0002026265,0.9460376,0.03552715,0.003660429,0.01107028,0.00003940903],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.238354,0.001807555,0.718838,0.001440155,0.001168087,0.000598361,0.001813466,0.01696651,0.01901377],"genre_scores_gemma":[0.9246661,0.0002561264,0.06891529,0.0002569232,0.0000926334,0.00007315064,0.0006146993,0.00008092723,0.005044224],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006556841,"threshold_uncertainty_score":0.01554948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02721084095044107,"score_gpt":0.2407248243737968,"score_spread":0.2135139834233557,"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."}}