{"id":"W2069923608","doi":"10.1016/j.jconhyd.2005.12.005","title":"Quantitative imaging of contaminant distributions in heterogeneous porous media laboratory experiments","year":2006,"lang":"en","type":"article","venue":"Journal of Contaminant Hydrology","topic":"Groundwater flow and contamination studies","field":"Environmental Science","cited_by":60,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University; Golder Associates (Canada)","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Porous medium; Permeability (electromagnetism); Visualization; TRACER; Scale (ratio); Biological system; Porosity; Environmental science; Geology; Computer science; Chemistry; Geotechnical engineering; Physics; Data mining","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000525767,0.0001840933,0.0005309811,0.0001551819,0.00007945555,0.00001187206,0.0002427733,0.00006894945,0.0001283456],"category_scores_gemma":[0.00007817797,0.0001532673,0.0001003898,0.0002260721,0.0003841723,0.0002665855,0.0001103561,0.0001743515,0.00002194714],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002354693,"about_ca_system_score_gemma":0.00003658087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006187489,"about_ca_topic_score_gemma":0.001168386,"domain_scores_codex":[0.9980084,0.0002047616,0.0009257061,0.0001945726,0.0003281148,0.0003384947],"domain_scores_gemma":[0.9988362,0.0002025638,0.000654839,0.0001441867,0.0001002247,0.00006198146],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004043757,0.0009060989,0.7825761,0.00001510779,0.00009053327,0.001359059,0.003001777,0.0005480376,0.2025414,0.0019471,0.0008336693,0.005776706],"study_design_scores_gemma":[0.004085913,0.001111094,0.9105762,0.00008540146,0.0001138016,0.0005301611,0.001644265,0.0008714889,0.068547,0.0006720631,0.01132481,0.0004377823],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9905767,0.001257942,0.007106349,0.0002485423,0.0003607806,0.0001156034,0.00003026127,0.000006172951,0.000297588],"genre_scores_gemma":[0.9993604,0.00004618225,0.000367731,0.00006599452,0.00003863882,0.000009655337,0.000007223205,0.00001135603,0.00009276321],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1339944,"threshold_uncertainty_score":0.625006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009156314508543891,"score_gpt":0.2475636938519463,"score_spread":0.2384073793434024,"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."}}