{"id":"W4223898140","doi":"10.1111/gwmr.12521","title":"Graphical Shading Logs: An Improved Approach for Collecting High Resolution Sedimentological Data at Contaminated Sites","year":2022,"lang":"en","type":"article","venue":"Groundwater Monitoring & Remediation","topic":"Groundwater flow and contamination studies","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; McGill University; Boeing","keywords":"Hydrogeology; Siliciclastic; Well logging; Geology; Database; Data collection; Bedrock; Data quality; Computer science; Data mining; Remote sensing; Facies; Engineering; Petroleum engineering; Geotechnical engineering; Geomorphology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001257047,0.0002331794,0.0002477004,0.0001041511,0.001829872,0.0001221538,0.0005392206,0.00009686381,0.0001223308],"category_scores_gemma":[0.00009280849,0.0002215593,0.00005579481,0.0003838212,0.00009909026,0.0007637013,0.001215463,0.0002169727,0.000007852802],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001091536,"about_ca_system_score_gemma":0.00001001532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004613041,"about_ca_topic_score_gemma":0.00007659086,"domain_scores_codex":[0.9973846,0.0002544306,0.0004143772,0.0008622276,0.0005730467,0.0005112912],"domain_scores_gemma":[0.9990469,0.0001398922,0.0001955937,0.0004723363,0.00004005387,0.000105223],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005481663,0.0007884286,0.5261052,0.00004915045,0.0001320903,0.000009244758,0.004491778,0.001571137,0.4483491,0.00009613348,0.001512058,0.01634746],"study_design_scores_gemma":[0.006504347,0.002813518,0.6696846,0.0000185617,0.0003665798,0.00006657463,0.007204166,0.2514343,0.03923799,0.0005288782,0.02028088,0.001859569],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9403021,0.00003855102,0.0576724,0.0001533889,0.0008373412,0.0007317754,0.00003749325,0.0001706899,0.00005628564],"genre_scores_gemma":[0.9906151,0.000005734841,0.005272225,0.00005271707,0.0003785067,0.0006119132,0.001816808,0.00002855436,0.001218411],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4091111,"threshold_uncertainty_score":0.9994696,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05690567007340305,"score_gpt":0.2739047524104742,"score_spread":0.2169990823370711,"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."}}