{"id":"W2039810161","doi":"10.1007/s11242-010-9612-x","title":"Statistical Synthesis of Imaging and Porosimetry Data for the Characterization of Microstructure and Transport Properties of Sandstones","year":2010,"lang":"en","type":"article","venue":"Transport in Porous Media","topic":"NMR spectroscopy and applications","field":"Physics and Astronomy","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph; University of Waterloo","funders":"University of Guelph","keywords":"Porosimetry; Microstructure; Fractal; Porous medium; Fractal dimension; Permeability (electromagnetism); Porosity; Materials science; Mineralogy; Geology; Hydrogeology; Characterization (materials science); Geotechnical engineering; Composite material; Nanotechnology; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001292368,0.00008088945,0.0002085269,0.00002924469,0.00002918168,0.00000241709,0.0001312897,0.00002483612,0.00002960835],"category_scores_gemma":[0.000005831011,0.00005766329,0.00001627238,0.00005776757,0.0002638652,0.00007700574,0.000006941501,0.00008261894,2.50387e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":9.130805e-7,"about_ca_system_score_gemma":0.00003644833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002857214,"about_ca_topic_score_gemma":0.00009107745,"domain_scores_codex":[0.999406,0.000005108306,0.0002863423,0.0001445879,0.00007030295,0.00008764137],"domain_scores_gemma":[0.999503,0.000102043,0.0001163304,0.0002257115,0.0000295738,0.00002335687],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0000504407,0.00004995514,0.3525673,0.0001097627,0.0000175564,1.446191e-7,0.0006743316,3.449464e-7,0.6373281,0.003750004,0.000001370164,0.005450609],"study_design_scores_gemma":[0.0002248691,0.000007298297,0.7003133,0.00003870412,0.00009925141,9.744257e-7,0.0002474123,0.000104139,0.2983927,0.0004508309,0.00005943479,0.00006111912],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9897184,0.00009390833,0.006542197,0.0001053317,0.00003821685,0.0002500089,0.003228677,0.000003223797,0.00002007016],"genre_scores_gemma":[0.9982504,0.00003199159,0.00129344,0.000004492775,0.00003562797,0.00002252731,0.0003491623,0.000009587327,0.000002789001],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.347746,"threshold_uncertainty_score":0.2351441,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01005597440034926,"score_gpt":0.2682547880365433,"score_spread":0.2581988136361941,"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."}}