{"id":"W4408392825","doi":"10.1016/j.renene.2025.122906","title":"Enabling fractured-vuggy reservoirs for large-scale gas storage: Green hydrogen, natural gas, and carbon dioxide","year":2025,"lang":"en","type":"article","venue":"Renewable Energy","topic":"Hydraulic Fracturing and Reservoir Analysis","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Sichuan Province Science and Technology Support Program; Alberta Innovates; National Outstanding Youth Science Fund Project of National Natural Science Foundation of China; Department of Science and Technology of Sichuan Province; National Natural Science Foundation of China; Energi Simulation","keywords":"Carbon dioxide; Natural gas; Environmental science; Petroleum engineering; Scale (ratio); Hydrogen; Hydrogen storage; Hydrogen sulphide; Waste management; Chemistry; Geology; Engineering; Organic chemistry; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002598022,0.0001790282,0.0002482737,0.0002062582,0.0004944173,0.000893739,0.0005612029,0.0005075824,0.001836325],"category_scores_gemma":[0.000556096,0.000186175,0.0001972996,0.0002766784,0.0006108001,0.001399103,0.001110105,0.0006009165,0.0002211948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000586364,"about_ca_system_score_gemma":0.001164618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002835719,"about_ca_topic_score_gemma":0.00775433,"domain_scores_codex":[0.9999052,0.00001034584,0.000003473247,0.00001182581,0.00004194139,0.00002720193],"domain_scores_gemma":[0.9998984,0.00002994793,0.00001075499,0.00002001926,0.00002759401,0.00001331738],"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":[0.0009177887,0.0002361302,0.009563847,0.0004067167,0.00008248818,0.0008366433,0.0004123359,0.3036125,0.4414096,0.1063468,0.005772795,0.1304022],"study_design_scores_gemma":[0.0000488891,0.0003158817,0.001862287,0.00004564612,0.00002117824,0.0001721084,0.0002782096,0.7348216,0.2315472,0.0202334,0.0105834,0.00007021063],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8349118,0.001052743,0.152123,0.001182105,0.0001908314,0.00004406301,0.0005334369,0.001413098,0.00854892],"genre_scores_gemma":[0.9847615,0.0001752818,0.01382015,0.00002777777,0.000004988026,0.00001261432,0.00007990888,0.00003089606,0.001087105],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002835719,"threshold_uncertainty_score":0.006143153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004357402383944844,"score_gpt":0.2065804841504957,"score_spread":0.2022230817665509,"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."}}