{"id":"W2793984285","doi":"10.1071/aseg2018abp055","title":"Drained pore modulus determination using digital rock technology","year":2018,"lang":"en","type":"article","venue":"ASEG Extended Abstracts","topic":"Hydraulic Fracturing and Reservoir Analysis","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Poromechanics; Geomechanics; Geology; Pore water pressure; Compaction; Bulk modulus; Modulus; Geotechnical engineering; Deformation (meteorology); Representative elementary volume; Volume (thermodynamics); Mineralogy; Materials science; Porosity; Porous medium; Composite material","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0001699338,0.0003649173,0.0002710623,0.0008556821,0.0002071492,0.0006967856,0.000606586,0.0004885969,0.00337996],"category_scores_gemma":[0.0007765571,0.0002782489,0.0004082606,0.0005228788,0.0003450626,0.0006096997,0.0005355566,0.0002857069,0.0007931598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004145312,"about_ca_system_score_gemma":0.0006573905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003328076,"about_ca_topic_score_gemma":0.006164778,"domain_scores_codex":[0.9998422,0.000005454427,0.00001168708,0.00003242958,0.00009313741,0.00001520879],"domain_scores_gemma":[0.9997599,0.00006608877,0.00005422583,0.00004889597,0.00005458648,0.00001640949],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000278036,0.0002023201,0.02435664,0.000639234,0.00006830614,0.000635744,0.0003926026,0.3871335,0.3986482,0.01256537,0.003873275,0.1712067],"study_design_scores_gemma":[0.00003104804,0.0001289859,0.01151045,0.0000354868,0.00003031655,0.0003312344,0.0001421404,0.7793458,0.1930394,0.004270413,0.01106741,0.0000672688],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4597252,0.0002550314,0.5134876,0.0002139464,0.00005383582,0.000256793,0.004897238,0.008247842,0.01286243],"genre_scores_gemma":[0.7562047,0.0002749446,0.2379355,0.00003469292,0.000005157621,0.0001465313,0.002169916,0.0003036899,0.002924881],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00337996,"threshold_uncertainty_score":0.01130712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008124569983207531,"score_gpt":0.2332216721024269,"score_spread":0.2250971021192194,"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."}}