{"id":"W2146897113","doi":"10.1029/2007wr006375","title":"A view toward the future of subsurface characterization: CAT scanning groundwater basins","year":2008,"lang":"en","type":"article","venue":"Water Resources Research","topic":"Geophysical Methods and Applications","field":"Engineering","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Strategic Environmental Research and Development Program","keywords":"Characterization (materials science); Structural basin; Scale (ratio); Remote sensing; Geology; Groundwater; Earth science; Environmental science; Geophysics; Hydrology (agriculture); Geomorphology; Geography; Cartography; Geotechnical 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":[0.0004560617,0.000111121,0.000165512,0.00007206049,0.0002610183,0.0000477993,0.0003759738,0.00006030522,0.0001102822],"category_scores_gemma":[0.00000682294,0.00006133213,0.00006021923,0.0003736293,0.0001938417,0.00007832074,0.0001127261,0.0002701766,0.0001324537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002722474,"about_ca_system_score_gemma":0.000007458901,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004056713,"about_ca_topic_score_gemma":0.000006977441,"domain_scores_codex":[0.9986565,0.0001743469,0.0001959447,0.0001699047,0.0004061905,0.0003971708],"domain_scores_gemma":[0.9993525,0.00006828163,0.00001334609,0.0003701861,0.0001205947,0.00007514585],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002438748,0.0001021605,0.002235474,0.0003338646,0.00006861391,0.00001262073,0.04380174,0.0005467785,0.9268602,0.0003367606,0.0005856172,0.02509179],"study_design_scores_gemma":[0.0001929249,0.00006666416,0.052731,0.00005437063,0.000008642294,0.00002102502,0.0007620785,0.00202317,0.1159173,0.0003347191,0.827669,0.0002191597],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954858,0.0002799548,0.0008529825,0.002158666,0.00006083503,0.0002553213,0.00000934489,0.00006733828,0.0008297081],"genre_scores_gemma":[0.997787,0.0002420083,0.0006288059,0.00002362418,0.0003546924,0.00008371801,0.00002081878,0.0000304388,0.0008289163],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8270833,"threshold_uncertainty_score":0.2501052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06163271581811052,"score_gpt":0.3106653082117415,"score_spread":0.249032592393631,"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."}}