{"id":"W2783089773","doi":"10.1007/s10596-017-9711-7","title":"Calibration of categorical simulations by evolutionary gradual deformation method","year":2018,"lang":"en","type":"article","venue":"Computational Geosciences","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Calibration; Facies; Categorical variable; Algorithm; Deformation (meteorology); Computer science; Hydrogeology; Geology; Mathematics; Statistics; Geotechnical engineering; Machine learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001679735,0.0005065891,0.0007697535,0.001207227,0.0006622542,0.001271417,0.002093922,0.001798672,0.002532707],"category_scores_gemma":[0.01419288,0.0006041422,0.00064442,0.00115328,0.001290232,0.001483425,0.001751677,0.001559329,0.00046977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009478457,"about_ca_system_score_gemma":0.001218716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006666528,"about_ca_topic_score_gemma":0.003672683,"domain_scores_codex":[0.9990962,0.0004065004,0.00005603159,0.0001875132,0.0001800851,0.00007381457],"domain_scores_gemma":[0.9955727,0.002189458,0.0003810619,0.0009064415,0.0007562905,0.0001941226],"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":[0.00001954452,0.00001330631,0.00105214,0.00001115532,0.00001081819,0.00001829722,0.00001983101,0.9898843,0.0002920475,0.005182748,0.00009446863,0.003401421],"study_design_scores_gemma":[0.000003942262,0.000003502046,0.0001036392,0.000001811616,0.000001104292,0.000003352397,0.000002932514,0.9983004,0.0001057879,0.001370985,0.00009966326,0.000002903916],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2354863,0.0001267678,0.7562867,0.0003487908,0.0001360963,0.00008124688,0.0003746446,0.001019229,0.006140105],"genre_scores_gemma":[0.932117,0.0000608236,0.06657211,0.0000450103,0.00002057164,0.0000929148,0.0002868155,0.0001680281,0.0006368365],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006666528,"threshold_uncertainty_score":0.01325548,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02212172335968821,"score_gpt":0.3040977431483299,"score_spread":0.2819760197886417,"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."}}