{"id":"W2792901377","doi":"10.4095/306491","title":"Using Oil, Gas and Salt Resources Library well data in groundwater research","year":2018,"lang":"en","type":"report","venue":"","topic":"Geological Modeling and Analysis","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Groundwater; Petroleum engineering; Groundwater resources; Salt (chemistry); Environmental science; Fossil fuel; Water resource management; Aquifer; Waste management; Geology; Engineering; Chemistry; Geotechnical engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002888421,0.0002014492,0.0004075266,0.0004620805,0.0002190671,0.0003460249,0.0008011371,0.0003354821,0.01229777],"category_scores_gemma":[0.0001857383,0.0001283825,0.0000435555,0.0004567009,0.0002895397,0.0003814245,0.0003650713,0.0006154969,0.0003874368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004665528,"about_ca_system_score_gemma":0.0002212279,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.08296674,"about_ca_topic_score_gemma":0.0208267,"domain_scores_codex":[0.9969217,0.0003405758,0.0004012917,0.0008835169,0.0009133348,0.0005395605],"domain_scores_gemma":[0.9986374,0.0002572902,0.00007886095,0.0007759158,0.00008403029,0.0001664774],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003813108,0.00003477085,0.8912631,0.0002181893,0.00006286091,0.0001833402,0.00009312173,0.000583011,0.000001201372,0.000001714713,0.05147622,0.05604431],"study_design_scores_gemma":[0.0001142708,0.000131842,0.02581347,0.0002713198,0.00005425459,0.00006846739,0.0001997113,0.182973,0.000002211278,0.001126917,0.7888278,0.0004167636],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5426186,0.00816387,0.0000387892,0.0008288532,0.0002872503,0.0000791484,0.0001546283,0.00007370197,0.4477552],"genre_scores_gemma":[0.8365973,0.02372881,0.008907635,0.0002723275,0.002503431,8.61237e-7,0.00511633,0.00002349231,0.1228498],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8654497,"threshold_uncertainty_score":0.9970406,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2884258622836004,"score_gpt":0.358124644410181,"score_spread":0.06969878212658065,"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."}}