{"id":"W1821079881","doi":"","title":"MODELING AND RHEOLOGICAL CHARACTERIZATION OF SLUDGE BASED DRILLING OIL","year":2016,"lang":"en","type":"article","venue":"DergiPark (Istanbul University)","topic":"Drilling and Well Engineering","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carbon Engineering (Canada)","funders":"","keywords":"Rheology; Characterization (materials science); Petroleum engineering; Drilling fluid; Drilling; Materials science; Environmental science; Biochemical engineering; Chemical engineering; Geology; Engineering; Nanotechnology; Metallurgy; Composite material","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":[0.0001827172,0.0005952232,0.0003725589,0.0004592021,0.000323862,0.0008054068,0.0004537773,0.0009493388,0.0007649543],"category_scores_gemma":[0.0004293014,0.0002374856,0.0004967459,0.0002857728,0.0002721518,0.000495364,0.0002807354,0.0002873018,0.0002454991],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003867926,"about_ca_system_score_gemma":0.0004062643,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006267092,"about_ca_topic_score_gemma":0.002458415,"domain_scores_codex":[0.9999141,0.00002046666,0.000007338721,0.00001853022,0.00002377841,0.00001579452],"domain_scores_gemma":[0.9998736,0.00004710086,0.00001882659,0.00001131835,0.00004046598,0.000008693959],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009239846,0.0000609637,0.002968108,0.00009913379,0.00001440585,0.0001860926,0.00006592137,0.9716366,0.01906278,0.0004690493,0.0001332255,0.005211358],"study_design_scores_gemma":[0.000003909961,0.00003747402,0.0005420051,0.000004251044,0.000004745884,0.00001620649,0.00001259692,0.9961807,0.002843696,0.0001264061,0.0002234817,0.000004696596],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.861953,0.0005299238,0.1297468,0.0001581412,0.00003685934,0.00008950865,0.0004267906,0.0003179795,0.006740985],"genre_scores_gemma":[0.9942554,0.0001526015,0.003432145,0.000005978191,0.000003531832,0.0000434723,0.0001456522,0.00001348916,0.001947749],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006267092,"threshold_uncertainty_score":0.01246125,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006822782163880375,"score_gpt":0.1450314794905561,"score_spread":0.1382086973266758,"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."}}