{"id":"W3014424289","doi":"10.1002/opfl.1349","title":"Dog Sniffs Out Leaks to Reduce Nonrevenue Water","year":2020,"lang":"en","type":"article","venue":"Opflow","topic":"Water Quality Monitoring Technologies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Leak; Business; Operations management; Engineering; Environmental engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000130026,0.0001149133,0.0001177409,0.00001368527,0.00007083656,0.00003839233,0.0004784343,0.00007251851,0.0004872025],"category_scores_gemma":[0.00007118832,0.00008725196,0.00003735106,0.00009024999,0.00007959895,0.000102674,0.0006166559,0.0001373722,0.01356727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007609442,"about_ca_system_score_gemma":0.000002536405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001105801,"about_ca_topic_score_gemma":0.00001000931,"domain_scores_codex":[0.998984,0.00002941107,0.0001326414,0.0003280943,0.0002168009,0.0003090089],"domain_scores_gemma":[0.9995186,0.00001068492,0.00001618269,0.0003270814,0.000003296403,0.0001241985],"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":[0.00002523508,0.00004923762,0.01380637,0.00001668147,0.0000126913,0.00004829337,0.007924293,0.0007464267,0.8715558,0.00002313935,0.08301727,0.02277459],"study_design_scores_gemma":[0.0001265084,0.0000961351,0.006123859,0.000009493067,0.000005175727,0.000001823734,0.0001136537,0.00005977481,0.7658039,0.0005256219,0.2269193,0.0002147955],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.964967,0.000005605667,0.0003801197,0.0310574,0.0003383376,0.0001683216,0.000006675364,0.0002860406,0.002790563],"genre_scores_gemma":[0.9917713,0.000002082998,0.004904015,0.0007704409,0.0001676977,0.00002039528,0.000003081569,0.00001680244,0.002344143],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.143902,"threshold_uncertainty_score":0.9872008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04964498146889235,"score_gpt":0.28135225437653,"score_spread":0.2317072729076377,"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."}}