{"id":"W4409497064","doi":"10.1016/j.energy.2025.136144","title":"Enhancing CO2 hydrate sequestration through underlying methane hydrate production: A novel strategy for carbon storage","year":2025,"lang":"en","type":"article","venue":"Energy","topic":"Methane Hydrates and Related Phenomena","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"China Geological Survey; Institute of Geology and Geophysics, Chinese Academy of Sciences; China Scholarship Council; Guangdong Science and Technology Department; Chinese Academy of Sciences; National Natural Science Foundation of China","keywords":"Hydrate; Carbon sequestration; Methane; Clathrate hydrate; Environmental science; Carbon capture and storage (timeline); Production (economics); Carbon dioxide; Enhanced coal bed methane recovery; Carbon fibers; Waste management; Petroleum engineering; Process engineering; Chemistry; Materials science; Climate change; Engineering; Geology; Oceanography","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":[0.00007130571,0.0003095427,0.0001986053,0.0001144603,0.0001565024,0.000352485,0.0002942675,0.0004030195,0.001203116],"category_scores_gemma":[0.00008534552,0.00009168483,0.0001658182,0.0001319068,0.0002609444,0.0005604484,0.0003647566,0.0003974664,0.0002797358],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000294191,"about_ca_system_score_gemma":0.0001958843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004118713,"about_ca_topic_score_gemma":0.0008871264,"domain_scores_codex":[0.9999657,0.000002910836,0.000001328837,0.000009593961,0.000007769797,0.0000127697],"domain_scores_gemma":[0.9999778,0.000005017738,0.000004330853,0.000003089577,0.000003667046,0.000006068778],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001355329,0.00007131668,0.0003168964,0.000230868,0.00001999038,0.0001660286,0.00002570108,0.001610316,0.9780279,0.007700341,0.0006575175,0.01103772],"study_design_scores_gemma":[0.00002675972,0.0002233496,0.0007560287,0.000008558443,0.00002117876,0.0001261159,0.00005282032,0.02187052,0.964862,0.002330472,0.009702266,0.00001978329],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9208354,0.007382757,0.04928819,0.001886641,0.0005795988,0.00008153481,0.0004096139,0.0005193912,0.01901696],"genre_scores_gemma":[0.9948615,0.0009687632,0.002670673,0.00005606785,0.00002111212,0.00001349999,0.00005801447,0.00001027019,0.001339989],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001203116,"threshold_uncertainty_score":0.004024863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03557746996001571,"score_gpt":0.2799074256805196,"score_spread":0.2443299557205039,"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."}}