{"id":"W2532768253","doi":"10.1139/cgj-2016-0235","title":"Thermal properties of oil sands fluid fine tailings: laboratory and in situ testing methods","year":2016,"lang":"en","type":"article","venue":"Canadian Geotechnical Journal","topic":"Petroleum Processing and Analysis","field":"Chemistry","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; Syncrude","keywords":"Tailings; Oil sands; Asphalt; Environmental science; Groundwater; Fast Fourier transform; Geotechnical engineering; Tailings dam; Geology; Thermal; Thermal conductivity; Mining engineering; Petroleum engineering; Materials science; Metallurgy; Composite material; Meteorology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0004557651,0.0005675531,0.0003008985,0.000550904,0.0003901405,0.000415031,0.0006153135,0.0004941824,0.001575162],"category_scores_gemma":[0.0009619843,0.000244442,0.0003443857,0.0004884644,0.0004031693,0.000541913,0.0002956091,0.0003702272,0.0004603663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004614191,"about_ca_system_score_gemma":0.0002675374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002244283,"about_ca_topic_score_gemma":0.00416613,"domain_scores_codex":[0.9993531,0.00006650729,0.00005369631,0.0001275004,0.0003466526,0.00005251575],"domain_scores_gemma":[0.9992896,0.0001902016,0.0001222619,0.00007616663,0.0002845479,0.00003717322],"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":[0.0002072221,0.0001600441,0.002567017,0.0001066788,0.000008503358,0.0000707361,0.0001992289,0.001064404,0.9885782,0.00006474417,0.00008907479,0.006884224],"study_design_scores_gemma":[0.0000104549,0.0005668671,0.003430753,0.000007685987,0.00001612548,0.00007664997,0.0001319865,0.003189271,0.9917326,0.00003921448,0.0007821534,0.00001633998],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9779919,0.0002406909,0.01824851,0.00004913713,0.00003563043,0.0001945989,0.0006323687,0.0001741392,0.002432894],"genre_scores_gemma":[0.9831882,0.0002905058,0.01308046,0.00002811315,0.00001524028,0.0002051744,0.0002847522,0.00003915117,0.002868372],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002244283,"threshold_uncertainty_score":0.005269468,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0196293456041824,"score_gpt":0.2517757314819852,"score_spread":0.2321463858778028,"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."}}