{"id":"W2604983094","doi":"","title":"Value of borehole data on geologic model construction for improving model calibration accuracy","year":2008,"lang":"en","type":"article","venue":"International Conference on Multimedia Information Networking and Security","topic":"Geological Modeling and Analysis","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Nuclear Waste Management Organization","funders":"","keywords":"Borehole; Calibration; Value (mathematics); Computer science; Data modeling; Geology; Remote sensing; Environmental science; Geotechnical engineering; Statistics; Mathematics; Machine learning; Database","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":[0.003461089,0.001180148,0.0007834843,0.002410706,0.0006496193,0.001065937,0.001336687,0.001260344,0.001926696],"category_scores_gemma":[0.03104409,0.0008287663,0.0005946893,0.002208179,0.0005911709,0.003890337,0.001217762,0.001094489,0.0007714844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005208036,"about_ca_system_score_gemma":0.001052056,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01146802,"about_ca_topic_score_gemma":0.01830508,"domain_scores_codex":[0.9982312,0.0006649656,0.0002054842,0.0003241194,0.0004617924,0.0001123376],"domain_scores_gemma":[0.9752672,0.01183649,0.001202954,0.006305721,0.005191809,0.0001957333],"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":[0.0009464768,0.000408702,0.1290641,0.000328829,0.0002568817,0.0003351982,0.0002509889,0.6028603,0.03362194,0.00392673,0.003286615,0.2247133],"study_design_scores_gemma":[0.0001268028,0.0000981785,0.04698995,0.00007822309,0.0001924006,0.0001561874,0.0001020328,0.9087098,0.03786197,0.002256904,0.003348114,0.00007948797],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6773221,0.0005050334,0.3055562,0.0005009899,0.000191239,0.0000865981,0.005522914,0.004273184,0.006041646],"genre_scores_gemma":[0.9338208,0.0001531775,0.06278709,0.00004633402,0.00003540647,0.00003001831,0.002516321,0.0002929847,0.0003178096],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01146802,"threshold_uncertainty_score":0.02280253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0801852305249233,"score_gpt":0.2754180318097034,"score_spread":0.1952328012847801,"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."}}