{"id":"W2762348911","doi":"10.1039/c7sc03466k","title":"From cellulose to kerogen: molecular simulation of a geological process","year":2017,"lang":"en","type":"article","venue":"Chemical Science","topic":"Hydrocarbon exploration and reservoir analysis","field":"Engineering","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Nautical Research Society","funders":"Air Force Office of Scientific Research; Aix-Marseille Université; Agence Nationale de la Recherche; National Science Foundation","keywords":"Kerogen; Molecular dynamics; Cellulose; Organic matter; Process (computing); Materials science; Chemical engineering; Chemistry; Geology; Organic chemistry; Source rock; Computational chemistry; Paleontology; Computer science; Engineering","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":[0.0002548977,0.0003328422,0.000543285,0.0003129265,0.0004679,0.0006480307,0.0008156574,0.001166463,0.002034718],"category_scores_gemma":[0.0009940777,0.0002460789,0.0004353136,0.0004213925,0.0007307366,0.0005265371,0.0005539836,0.0007951906,0.0001367391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007328703,"about_ca_system_score_gemma":0.0009616324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0131476,"about_ca_topic_score_gemma":0.006461879,"domain_scores_codex":[0.9999201,0.00002131793,0.000002426967,0.00001006408,0.00001771842,0.00002839465],"domain_scores_gemma":[0.9996341,0.0002301724,0.00002555104,0.00002555552,0.0000388503,0.0000457541],"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":[0.00009727685,0.00008843308,0.001323059,0.00002940886,0.00002202122,0.00007880876,0.00005551958,0.9900449,0.002186893,0.00440642,0.0001953341,0.00147199],"study_design_scores_gemma":[0.00001956579,0.00002085852,0.0001667588,0.000001906279,0.00000271553,0.000003561989,0.00001261186,0.9988366,0.0003092574,0.0004382951,0.0001847051,0.000003171082],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9795495,0.0001395932,0.01251222,0.0003531385,0.00004630374,0.00004684897,0.0002660198,0.0001231056,0.006963173],"genre_scores_gemma":[0.9881902,0.0001894738,0.009180561,0.00009996963,0.00001297849,0.0001030585,0.0003089636,0.00004354121,0.001871228],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0131476,"threshold_uncertainty_score":0.02614212,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0162987139074506,"score_gpt":0.2822430271689641,"score_spread":0.2659443132615135,"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."}}