{"id":"W4406001006","doi":"10.1186/s13021-024-00289-7","title":"Integrating territorial pattern changes into the relationship between carbon sequestration and water yield in the Yangtze River Basin, China","year":2025,"lang":"en","type":"article","venue":"Carbon Balance and Management","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"Natural Science Foundation of Hainan Province; National Natural Science Foundation of China","keywords":"Ecosystem services; Ecosystem; Sustainable development; Environmental science; Carbon sequestration; China; Production (economics); Structural basin; Primary production; Yield (engineering); Ecology; Water resource management; Geography; Environmental resource management; Geology; Economics","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":[0.0003608324,0.00008963256,0.00008468881,0.00002659899,0.0001140979,0.00006833001,0.0001276799,0.00003904005,0.000004231548],"category_scores_gemma":[0.000006158215,0.00004425143,0.00001017292,0.0000840293,0.00002555275,0.00006948807,0.0001300833,0.00009184472,0.000001577786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003408894,"about_ca_system_score_gemma":0.000001142395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00651357,"about_ca_topic_score_gemma":0.007680838,"domain_scores_codex":[0.999396,0.00006589256,0.0001136,0.0001815416,0.0001102549,0.0001327601],"domain_scores_gemma":[0.9997398,0.00006631849,0.00002735975,0.0001509988,0.000001741123,0.00001377239],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000003452371,0.000005334665,0.9914854,0.00005802995,0.000007727549,0.000002711261,0.004294896,0.000006122797,0.00003877645,0.0001375408,0.00006291569,0.003897101],"study_design_scores_gemma":[0.0001705296,0.00002224083,0.9948612,0.0001057819,0.00002919676,3.227508e-7,0.0006962147,0.0008599468,0.0001056326,0.001474542,0.001601244,0.0000731806],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9881939,0.00007460375,0.00001960522,0.004575154,0.0001915239,0.0002928709,7.281191e-7,0.00001123984,0.006640382],"genre_scores_gemma":[0.9991972,0.00009383513,0.00001193272,0.0004079818,0.0001460869,0.00005569246,0.000007105687,0.00000323145,0.00007686198],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01100338,"threshold_uncertainty_score":0.9846612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01187797766137933,"score_gpt":0.222742494878692,"score_spread":0.2108645172173127,"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."}}