{"id":"W2058613436","doi":"10.2118/02-01-tb1","title":"Small Scale Simulation of Pipeline or Stirred Tank Conditioning of Oil Sands: Temperature and Mechanical Energy","year":2002,"lang":"en","type":"article","venue":"Journal of Canadian Petroleum Technology","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Asphalt; Conditioning; Air conditioning; Pipeline (software); Extraction (chemistry); Oil sands; Petroleum engineering; Pipeline transport; Environmental science; Process engineering; Waste management; Engineering; Materials science; Environmental engineering; Mechanical engineering; Chemistry; Chromatography; Composite material; Mathematics","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":[0.0001917214,0.0003950817,0.0003970632,0.0002642759,0.0004353736,0.0007157872,0.0006920841,0.001269739,0.006584767],"category_scores_gemma":[0.0006771491,0.0001988626,0.0007083734,0.0002367957,0.000430539,0.0003420767,0.000407191,0.0006492145,0.0003504013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007944257,"about_ca_system_score_gemma":0.0007495254,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02173679,"about_ca_topic_score_gemma":0.01782002,"domain_scores_codex":[0.9999098,0.00001385105,0.000004388731,0.00001625615,0.00002529009,0.00003043236],"domain_scores_gemma":[0.9995321,0.0003146446,0.0000294658,0.00002260853,0.0000632755,0.00003801618],"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":[0.0001626804,0.0001164572,0.00267589,0.00006953048,0.0000133358,0.0001504209,0.00003451656,0.9882097,0.006030616,0.0005343491,0.0002394485,0.00176306],"study_design_scores_gemma":[0.00003010312,0.0001541995,0.001561151,0.000007431501,0.00000950353,0.00001487901,0.00005331905,0.9945327,0.002892014,0.0001923177,0.0005423427,0.00001004557],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9779978,0.00008583404,0.008455142,0.000159578,0.00003923762,0.0001238027,0.001017656,0.0001800792,0.01194085],"genre_scores_gemma":[0.9928196,0.00005655113,0.00319166,0.00002541803,0.000003220691,0.00008762068,0.0003571709,0.00002342539,0.003435373],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9782632,"threshold_uncertainty_score":0.04322058,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01558047737276744,"score_gpt":0.220041362545342,"score_spread":0.2044608851725745,"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."}}