{"id":"W7111981163","doi":"","title":"ESTIMATION OF NITRATES IN SOUTHERN CALIFORNIA WATER RESOURCES","year":2025,"lang":"","type":"article","venue":"CSUSB ScholarWorks (California State University, San Bernardino)","topic":"Water Quality Monitoring and Analysis","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Water quality; Water resources; Nitrate; Contamination; Estimation; Water pollution; Agriculture; Pollution","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001754066,0.0006770547,0.0009693946,0.0009584213,0.000732724,0.0003112757,0.001303441,0.0004589215,0.001489699],"category_scores_gemma":[0.00009140559,0.0006400944,0.0005045759,0.001763973,0.000851367,0.0006249899,0.001224654,0.001194616,0.002252072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009887958,"about_ca_system_score_gemma":0.00006428167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006282271,"about_ca_topic_score_gemma":0.0002856783,"domain_scores_codex":[0.9948186,0.0008325346,0.001134077,0.001155208,0.0009035199,0.001156082],"domain_scores_gemma":[0.9980878,0.0001852862,0.0003954984,0.0008826448,0.00009800083,0.0003507933],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001274322,0.001194735,0.6148024,0.0006129482,0.0009187442,0.0002804648,0.01619991,0.2986067,0.02107043,0.00004463199,0.001143813,0.04385094],"study_design_scores_gemma":[0.02274553,0.0009594961,0.1470609,0.01002329,0.005893807,0.000040924,0.1226115,0.1787068,0.3265132,0.0197672,0.156053,0.00962432],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992011,0.0002836678,0.002155059,0.0008827216,0.000272624,0.0003903154,0.00193422,0.00008217217,0.001988299],"genre_scores_gemma":[0.9909403,0.0002401128,0.0005846127,0.00005497879,0.0000548322,0.000001778732,0.0001032095,0.00004419399,0.007975955],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4677415,"threshold_uncertainty_score":0.9996051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008067275704900845,"score_gpt":0.213874121645075,"score_spread":0.2058068459401742,"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."}}