{"id":"W2611312474","doi":"10.1155/2017/9562507","title":"Hydrothermal Dissolution of Deeply Buried Cambrian Dolomite Rocks and Porosity Generation: Integrated with Geological Studies and Reactive Transport Modeling in the Tarim Basin, China","year":2017,"lang":"en","type":"article","venue":"Geofluids","topic":"Hydrocarbon exploration and reservoir analysis","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"National Natural Science Foundation of China","keywords":"Dolomite; Geology; Dissolution; Hydrothermal circulation; Geochemistry; Carbonate; Permeability (electromagnetism); Carbonate rock; Porosity; Karst; Structural basin; Borehole; Tarim basin; Petrology; Mineralogy; Geomorphology; Geotechnical engineering; Sedimentary rock; Paleontology; Chemical 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":[0.00026866,0.0006283428,0.0004092917,0.0008989323,0.0004177369,0.0006693524,0.0007466748,0.0005419065,0.0003263234],"category_scores_gemma":[0.000452269,0.0003849009,0.0007306607,0.0007770627,0.0003758383,0.0006198531,0.0004657011,0.0002111134,0.00003571247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00174356,"about_ca_system_score_gemma":0.001429191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1882221,"about_ca_topic_score_gemma":0.110859,"domain_scores_codex":[0.9999152,0.00001084114,0.000008537825,0.00002965979,0.0000120793,0.00002360402],"domain_scores_gemma":[0.9998883,0.00003138472,0.0000261294,0.00001025483,0.00002264298,0.00002124496],"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":[0.0002159465,0.0002844992,0.3779459,0.0001129089,0.0001663495,0.0006445117,0.0004679913,0.5826803,0.01986945,0.0007873095,0.0001189101,0.016706],"study_design_scores_gemma":[0.00002095929,0.0000334356,0.05941841,0.000005098239,0.00003548816,0.00002407959,0.0001793406,0.9379913,0.002083879,0.0001155884,0.00007800209,0.00001452126],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994171,0.00002205524,0.0003558618,0.00001970961,8.087768e-7,0.000003402954,0.00004310614,0.00001329661,0.0001246755],"genre_scores_gemma":[0.9995427,0.00002833342,0.0002784515,0.000002000072,9.0333e-7,0.000002556014,0.00006166953,0.000002784961,0.00008067521],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1882221,"threshold_uncertainty_score":0.3742531,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03080010939652355,"score_gpt":0.2437531224836628,"score_spread":0.2129530130871393,"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."}}