{"id":"W4392159417","doi":"10.18280/i2m.230101","title":"Development and Evaluation of a MQ-5 Sensor-Based Condition Monitoring System for In-Situ Pipeline Leak Detection","year":2024,"lang":"en","type":"article","venue":"Instrumentation Mesure Métrologie","topic":"Fire Detection and Safety Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Leak; Leak detection; Pipeline (software); Computer science; In situ; Embedded system; Real-time computing; Environmental science; Engineering; Operating system; Chemistry; Environmental engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001435911,0.0004991319,0.0006295477,0.000464909,0.0003292374,0.0005693628,0.00124557,0.0008148635,0.001438776],"category_scores_gemma":[0.001470469,0.0002525893,0.0003671696,0.0002643003,0.0002588713,0.0008194584,0.0004605668,0.0003638006,0.0005054022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004504953,"about_ca_system_score_gemma":0.000808807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001681601,"about_ca_topic_score_gemma":0.001076337,"domain_scores_codex":[0.9989493,0.0001623299,0.00006879408,0.0002006618,0.0005396973,0.00007915062],"domain_scores_gemma":[0.9989741,0.0001218004,0.0001017397,0.00008711759,0.0006352381,0.00008007819],"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":[0.000538954,0.0006698707,0.007358104,0.0005814398,0.00006399153,0.0003500954,0.0005217383,0.005216762,0.9078603,0.0005130919,0.001225228,0.07510049],"study_design_scores_gemma":[0.0001981423,0.009268682,0.02442937,0.00007572336,0.0002767387,0.0008579792,0.0003580285,0.1232629,0.8255455,0.0001796634,0.01543106,0.0001162756],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.701789,0.0005087869,0.2894056,0.0003693249,0.0002112278,0.001170151,0.0002967849,0.003668547,0.002580509],"genre_scores_gemma":[0.8646435,0.0003269053,0.1294246,0.0001910638,0.0000356108,0.0003616609,0.0003158201,0.00008635605,0.004614444],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001681601,"threshold_uncertainty_score":0.00759387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04207945217635065,"score_gpt":0.3017368412906354,"score_spread":0.2596573891142847,"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."}}