{"id":"W4252893418","doi":"10.2523/77408-ms","title":"Low Field NMR Water Cut Metering","year":2002,"lang":"en","type":"article","venue":"Proceedings of SPE Annual Technical Conference and Exhibition","topic":"NMR spectroscopy and applications","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; Canadian Natural Resources","funders":"","keywords":"Metering mode; Environmental science; Water quality; Volume (thermodynamics); Materials science; Asphalt; Petroleum engineering; Process engineering; Geology; Engineering; Mechanical engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0006748186,0.0005150395,0.0004534875,0.0009444944,0.0003409531,0.0006734144,0.001077067,0.0005361343,0.003923051],"category_scores_gemma":[0.0008999371,0.0002378747,0.0001897751,0.0006255917,0.0004856717,0.001076489,0.0006153798,0.0006118125,0.001067696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006526178,"about_ca_system_score_gemma":0.0007261896,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002933813,"about_ca_topic_score_gemma":0.005823738,"domain_scores_codex":[0.9990803,0.0001013662,0.00002138343,0.0001049987,0.0006402201,0.00005171112],"domain_scores_gemma":[0.9992375,0.0001099502,0.00008737641,0.0001029591,0.0003977648,0.00006444212],"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":[0.0002444872,0.0001207218,0.005243309,0.0002008118,0.00001598102,0.0001146543,0.0001219557,0.00184342,0.7969978,0.001435379,0.002906442,0.1907551],"study_design_scores_gemma":[0.00008155239,0.0008874012,0.01165047,0.0000262987,0.00006828295,0.0006055966,0.00008424463,0.0259137,0.8975822,0.0006711487,0.06230565,0.0001234329],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3275475,0.0009140086,0.6386493,0.0005970806,0.00033384,0.0005971461,0.001629349,0.007822253,0.02190952],"genre_scores_gemma":[0.4566796,0.0007429999,0.5167008,0.0005839475,0.0001790537,0.0003744954,0.002001632,0.0004470802,0.02229035],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003923051,"threshold_uncertainty_score":0.01312393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0167452412260417,"score_gpt":0.2810417736805521,"score_spread":0.2642965324545104,"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."}}