{"id":"W2101151824","doi":"10.1144/1467-7873/03-019","title":"Finding deeply buried deposits using geochemistry","year":2004,"lang":"en","type":"article","venue":"Geochemistry Exploration Environment Analysis","topic":"Groundwater flow and contamination studies","field":"Environmental Science","cited_by":221,"is_retracted":false,"has_abstract":true,"ca_institutions":"Geological Survey of Canada","funders":"","keywords":"Geology; Groundwater; Vadose zone; Terrain; Mineral exploration; Arid; Geochemistry; Geological survey; Soil water; Mining engineering; Earth science; Soil science; Geophysics; Geotechnical engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001595702,0.000277398,0.000276398,0.00006525053,0.0004030448,0.00008009649,0.0002234784,0.0001133793,0.002399041],"category_scores_gemma":[0.00001644619,0.000294098,0.0002188023,0.0005419836,0.00015273,0.0004960935,0.0002238279,0.0001224725,0.0003370723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005971676,"about_ca_system_score_gemma":0.000009909812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001272893,"about_ca_topic_score_gemma":0.00004145069,"domain_scores_codex":[0.9980781,0.00002456698,0.0003865743,0.0005985181,0.0005569787,0.0003552753],"domain_scores_gemma":[0.9992068,0.00001620133,0.0001955044,0.0004397766,0.000009572731,0.0001321115],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002057704,0.000269645,0.0717624,0.00001960544,0.0007371383,0.00002878323,0.001296387,0.2709708,0.6519048,0.00001386173,0.0001867148,0.002789289],"study_design_scores_gemma":[0.001303576,0.00003571493,0.02649214,0.00002611754,0.001960564,0.00001339255,0.001670041,0.01044903,0.951211,0.0006227886,0.005105381,0.001110308],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7780417,0.00003952458,0.22025,0.0003315633,0.00002011188,0.0001240288,0.000006926883,0.00005211618,0.001133982],"genre_scores_gemma":[0.9945762,0.00003035574,0.003185318,0.00008781631,0.00007528199,0.00008197865,0.0002333884,0.00001598514,0.001713717],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2993062,"threshold_uncertainty_score":0.9999511,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01970030800873791,"score_gpt":0.2248638630562399,"score_spread":0.205163555047502,"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."}}