{"id":"W2292983827","doi":"10.1007/s12652-016-0362-7","title":"Wireless sensor networks for leak detection in pipelines: a survey","year":2016,"lang":"en","type":"article","venue":"Journal of Ambient Intelligence and Humanized Computing","topic":"Water Systems and Optimization","field":"Engineering","cited_by":76,"is_retracted":false,"has_abstract":false,"ca_institutions":"Acadia University","funders":"King Fahd University of Petroleum and Minerals","keywords":"Pipeline transport; Computer science; Focus (optics); Pipeline (software); Wireless; Wireless sensor network; Leak; Transient (computer programming); Leak detection; SIGNAL (programming language); Computer security; Telecommunications; Environmental science","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":[0.001418607,0.001005034,0.0009541475,0.001347172,0.0002751028,0.001183915,0.001575974,0.00117498,0.001864811],"category_scores_gemma":[0.002447764,0.0005310453,0.0007167899,0.002843305,0.0005285471,0.002438301,0.0008718793,0.0009509524,0.000732908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004335699,"about_ca_system_score_gemma":0.0006649785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001467883,"about_ca_topic_score_gemma":0.001563026,"domain_scores_codex":[0.9993175,0.0001466867,0.00006330977,0.0001867729,0.0002475054,0.00003825921],"domain_scores_gemma":[0.9979758,0.001280553,0.0001722876,0.000129883,0.0003918206,0.00004972764],"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":[0.0001438951,0.0002216595,0.004745346,0.005216199,0.0002515035,0.0001318639,0.0001271408,0.02937665,0.005547916,0.01821646,0.009051716,0.9269696],"study_design_scores_gemma":[0.0000719388,0.001263274,0.01243649,0.003704387,0.0006554786,0.002693263,0.001081383,0.2816277,0.02374836,0.04509414,0.6273658,0.0002578228],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.01676405,0.7502557,0.2116517,0.002608076,0.0007310014,0.0001468726,0.0002791282,0.0001910073,0.01737245],"genre_scores_gemma":[0.1316442,0.8058115,0.05427307,0.0007421086,0.001390781,0.0001244363,0.000399067,0.00004814377,0.005566738],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.001864811,"threshold_uncertainty_score":0.007502377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02925847341406986,"score_gpt":0.2416787867675856,"score_spread":0.2124203133535157,"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."}}