{"id":"W4399154135","doi":"10.1126/science.adn1262","title":"Human activities shape global patterns of decomposition rates in rivers","year":2024,"lang":"en","type":"article","venue":"Science","topic":"Freshwater macroinvertebrate diversity and ecology","field":"Environmental Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; University of British Columbia; University of Regina; Ontario Tech University; Trent University; University of Calgary; Memorial University of Newfoundland; International Institute for Sustainable Development; Queen's University; Université du Québec à Montréal; Wilfrid Laurier University","funders":"Division of Environmental Biology; University of Georgia Research Foundation; Office of Environmental Management; Celldex Therapeutics; U.S. Department of Energy; National Science Foundation","keywords":"Decomposition; Carbon cycle; Environmental science; Litter; Detritus; Scale (ratio); Plant litter; Variance decomposition of forecast errors; Ecology; Cellulose; Cycling; Variance (accounting); STREAMS; Ecosystem; Biology; Geography; Mathematics; Statistics; Computer science; Forestry; Cartography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003291857,0.0001518886,0.0002066448,0.0008200516,0.0001654089,0.0006381159,0.000129464,0.0002047828,0.001092756],"category_scores_gemma":[0.0008986262,0.0001628775,0.0003184061,0.0008258463,0.0004080622,0.0003392195,0.000461748,0.0001772648,0.0001832138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002357997,"about_ca_system_score_gemma":0.0001378464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009566481,"about_ca_topic_score_gemma":0.01565184,"domain_scores_codex":[0.999823,0.00005704261,0.00001245907,0.00007085526,0.00001286223,0.00002368852],"domain_scores_gemma":[0.999504,0.0001565291,0.0001725805,0.00005741364,0.00006984638,0.00003978019],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005403192,0.00001325335,0.9903648,0.00001277592,0.00008834018,0.00003388468,0.0003120123,0.002114275,0.001589399,0.0001302269,0.0001659701,0.005121048],"study_design_scores_gemma":[0.00000195548,0.000007125737,0.9968425,0.000004837655,0.00001136613,0.00001920089,0.0002475748,0.002492176,0.00007458346,0.0001450292,0.0001491937,0.000004486896],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989696,0.00006846501,0.0002399422,0.00002354547,9.619012e-7,0.000001624498,0.0002288747,0.00001385514,0.0004531173],"genre_scores_gemma":[0.9995529,0.00003896621,0.00009992057,0.000005475381,0.00000143533,0.000002247225,0.0002059453,0.000004407281,0.00008862517],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009566481,"threshold_uncertainty_score":0.01902163,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01044479493343249,"score_gpt":0.2612938956811367,"score_spread":0.2508491007477042,"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."}}