{"id":"W4407853091","doi":"10.1021/acsestwater.4c01054","title":"Urbanization Impacts Dissolved Organic Matter Concentration and Quality in a Southeastern United States Watershed","year":2025,"lang":"en","type":"article","venue":"ACS ES&T Water","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"University of South Carolina; Office for Coastal Management; National Oceanic and Atmospheric Administration; National Science Foundation","keywords":"Urbanization; Watershed; Environmental science; Organic matter; Dissolved organic carbon; Water quality; Water resource management; Hydrology (agriculture); Environmental chemistry; Geology; Chemistry; Ecology; Economics; Economic growth; Computer science","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002120457,0.0001058218,0.0001343617,0.00006299494,0.00005512185,0.0001201465,0.00007092028,0.00005152677,0.0009715112],"category_scores_gemma":[0.000009862595,0.00006819768,0.00001238684,0.0001708447,0.00002317243,0.0002009018,0.00002223008,0.0000646393,0.0001777953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004040089,"about_ca_system_score_gemma":0.00001180686,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008496229,"about_ca_topic_score_gemma":0.01448477,"domain_scores_codex":[0.9991263,0.0001142511,0.0002474156,0.0001826058,0.00009041333,0.0002390447],"domain_scores_gemma":[0.9997389,0.00003046317,0.0000323804,0.0001133074,0.00003312602,0.00005186311],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000507923,0.00000871752,0.9964156,0.00006026724,0.00001026813,0.000002160289,0.001459156,0.0000886297,0.001356878,0.00001723598,0.00009185155,0.000438448],"study_design_scores_gemma":[0.0006876844,0.00004026945,0.984817,0.00004334649,0.00001225113,0.000002020747,0.0006766506,0.005774146,0.005612828,0.0004830685,0.001677561,0.000173189],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977675,0.00003250175,0.0001072187,0.0008573697,0.00008915315,0.0001655344,0.00002640113,0.00002239876,0.0009318851],"genre_scores_gemma":[0.9966958,0.00001446286,0.000006520868,0.0006989312,0.0000176959,0.000001136017,0.00143061,0.000002967696,0.001131938],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01159861,"threshold_uncertainty_score":0.9999417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009303518488062443,"score_gpt":0.2091945416607677,"score_spread":0.1998910231727053,"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."}}