{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000270703,0.0001206743,0.0001566639,0.00009930201,0.0001789613,0.00005418605,0.0002496619,0.0001041023,0.00004160597],"category_scores_gemma":[0.0002512697,0.0001005011,0.0000426776,0.00006950779,0.00009355778,0.0007237575,0.00003311447,0.0001548145,0.000007061877],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006296924,"about_ca_system_score_gemma":0.00008796763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001759349,"about_ca_topic_score_gemma":0.00006911932,"domain_scores_codex":[0.9989437,0.00003128237,0.0003807477,0.0002103133,0.0002858685,0.0001480286],"domain_scores_gemma":[0.9990717,0.0001965425,0.0002723014,0.0001823606,0.0002123721,0.00006477327],"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":[0.0001025926,0.00001696667,0.004441377,0.00001262743,0.00001567615,3.641447e-7,0.0003850131,0.9311874,0.000005352807,0.00381414,0.00009619655,0.05992231],"study_design_scores_gemma":[0.0003537282,0.0000593823,0.0009445293,0.00002078125,0.00001256456,0.000006282798,0.00007023119,0.9875546,0.00003090296,0.01072458,0.0001105396,0.0001119272],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4899781,0.00005828281,0.4992323,0.001284506,0.0007676749,0.0003526816,0.001258032,0.0001018694,0.006966604],"genre_scores_gemma":[0.9830921,0.0002466077,0.0134742,0.0002297398,0.0001176357,0.000003234282,0.002817965,0.000001523469,0.00001697887],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4931141,"threshold_uncertainty_score":0.4098317,"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."}}