{"id":"W2062774896","doi":"10.1007/s10109-008-0066-4","title":"Minimizing the effects of inaccurate sediment description in borehole data using rough sets and transition probability","year":2008,"lang":"en","type":"article","venue":"Journal of Geographical Systems","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University; University of Guelph","funders":"Ministry of Education, India; Ministry of Earth Sciences","keywords":"Borehole; Geology; Silt; Lithology; Data mining; Metadata; Scheme (mathematics); Data quality; Standardization; Computer science; Geotechnical engineering; Petrology; Mathematics; Geomorphology; Metric (unit); 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00136536,0.00009664355,0.0002828948,0.000128234,0.0001023747,0.00007071724,0.0004986831,0.00006825017,1.75414e-7],"category_scores_gemma":[0.00007038293,0.00005851945,0.00006179941,0.0004683841,0.0001085066,0.0007198336,0.000107209,0.0002147793,8.214712e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002954411,"about_ca_system_score_gemma":0.00004287026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002871327,"about_ca_topic_score_gemma":0.000009032415,"domain_scores_codex":[0.9983293,0.0003593886,0.0005941602,0.0001866477,0.0003706068,0.0001599253],"domain_scores_gemma":[0.998942,0.0001763845,0.0003682161,0.0003534237,0.00009507111,0.00006486556],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001233313,0.006108148,0.7402581,0.008090018,0.001141181,0.002533169,0.04807742,0.05699587,0.05255203,0.01325612,0.002015771,0.06773888],"study_design_scores_gemma":[0.002653187,0.001226014,0.4224653,0.00148253,0.00008463422,0.002257721,0.0003006078,0.5645849,0.0002364457,0.004059739,0.0003168357,0.0003320785],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9604937,0.002063186,0.03633446,0.0004152956,0.0004020627,0.0002717242,0.000002513676,0.000006255536,0.00001075757],"genre_scores_gemma":[0.9938823,0.0002149126,0.00579973,0.00003789423,0.00005886323,0.000002002081,0.00000102706,0.000003063043,2.182142e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.507589,"threshold_uncertainty_score":0.2386354,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06342157768310094,"score_gpt":0.2601923267286866,"score_spread":0.1967707490455856,"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."}}