{"id":"W2088856899","doi":"10.1016/j.chemosphere.2008.04.036","title":"A first approximation kinetic model to predict methane generation from an oil sands tailings settling basin","year":2008,"lang":"en","type":"article","venue":"Chemosphere","topic":"Hydrocarbon exploration and reservoir analysis","field":"Engineering","cited_by":69,"is_retracted":false,"has_abstract":false,"ca_institutions":"Syncrude (Canada); University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Syncrude; Canadian Natural Resources Limited","keywords":"Naphtha; Tailings; Oil sands; Environmental chemistry; Microcosm; Methane; Chemistry; Environmental science; Organic chemistry; Materials science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008880561,0.0001804207,0.0002194278,0.00003186099,0.000102466,0.00004025632,0.000139936,0.0001258799,0.000149332],"category_scores_gemma":[0.00003324728,0.0001809794,0.00007224916,0.0003224459,0.00001675295,0.000271984,0.00001933858,0.0001248638,0.00005089518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007666308,"about_ca_system_score_gemma":0.00002343438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001003734,"about_ca_topic_score_gemma":0.0001879261,"domain_scores_codex":[0.9989967,0.00001756732,0.0002757312,0.0002718338,0.0002445184,0.0001936199],"domain_scores_gemma":[0.9994085,0.00001297851,0.00003143583,0.0003137259,0.00005975919,0.0001736111],"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":[0.000006578451,0.00002327024,0.0001119522,0.00002028045,0.00003413955,0.000002698637,0.001600054,0.9631018,0.03284203,0.000008249192,0.001310755,0.0009382156],"study_design_scores_gemma":[0.0002940693,0.00001423317,0.00005231463,0.00001722595,0.00003352262,0.000001736795,0.00008188636,0.9512892,0.04700559,0.00004978091,0.0009616525,0.0001987995],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8278197,0.0001632376,0.1700152,0.000305046,0.00007590025,0.00006757307,0.00001186771,0.0003191984,0.001222286],"genre_scores_gemma":[0.973038,0.0001183145,0.02545749,0.0001728661,0.0002742757,0.00005236717,0.000330997,0.00004532591,0.0005103498],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1452183,"threshold_uncertainty_score":0.7380128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0231003805070862,"score_gpt":0.2229180947833533,"score_spread":0.199817714276267,"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."}}