{"id":"W4313598658","doi":"10.48550/arxiv.2301.01757","title":"Molecular dynamics predictions of transport properties for carbon dioxide hydrates under pre-nucleation conditions using TIP4P/Ice water and EPM2, TraPPE, and Zhang carbon dioxide potentials","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Methane Hydrates and Related Phenomena","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Alliance de recherche numérique du Canada; Western Canada Research Grid","keywords":"Carbon dioxide; Viscosity; Nucleation; Molecular dynamics; Clathrate hydrate; Thermodynamics; Chemistry; Rheology; Water model; Thermal diffusivity; Chemical physics; Materials science; Hydrate; Physics; Computational chemistry; Organic chemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000225471,0.0005542738,0.0002390647,0.0003835281,0.0005546411,0.0003823366,0.0006509431,0.0008777567,0.002083244],"category_scores_gemma":[0.0009477828,0.0002552786,0.0003661655,0.0003486802,0.0003377899,0.0007337389,0.0003048966,0.0006456302,0.0002312393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001206208,"about_ca_system_score_gemma":0.001038162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01714828,"about_ca_topic_score_gemma":0.01013341,"domain_scores_codex":[0.9999405,0.00001044223,0.000002763703,0.00001081438,0.0000199582,0.00001561274],"domain_scores_gemma":[0.9997548,0.0001283054,0.00002165016,0.00001315313,0.00006146401,0.00002051523],"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":[0.0001015668,0.00007840241,0.002598588,0.0001078426,0.0000178118,0.0001546547,0.00008119732,0.9730753,0.01214973,0.006867073,0.001039117,0.003728786],"study_design_scores_gemma":[0.00001181075,0.00001101107,0.0002835568,0.000002908235,0.000001717323,0.000003963264,0.000007808651,0.996636,0.002510205,0.0003168129,0.0002102113,0.000003926946],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9634383,0.0003138009,0.02312251,0.0006272225,0.00006219096,0.00006463499,0.001367827,0.0002550457,0.0107485],"genre_scores_gemma":[0.9875101,0.0002422883,0.009334958,0.00004708211,0.00001938972,0.0001222818,0.0007517227,0.00008711702,0.001885065],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01714828,"threshold_uncertainty_score":0.03409696,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03903806832472753,"score_gpt":0.1844190736320901,"score_spread":0.1453810053073626,"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."}}