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Record W4404420811 · doi:10.1093/nsr/nwae414

Influence of global warming and human activity on mercury accumulation patterns in wetlands across the Qinghai–Tibet Plateau

2024· article· en· W4404420811 on OpenAlex
Xinbin Feng, Xun Wang, Longyu Jia, Wei Yuan, Lu Meng, Nantao Liu, Fei Wu, Xinyuan Cai, Fei Wang, Che-Jen Lin

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNational Science Review · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsUniversity of Manitoba
FundersNational Natural Science Foundation of China
KeywordsWetlandMercury (programming language)Plateau (mathematics)Environmental scienceQinghai lakeGlobal warmingPhysical geographyClimatologyClimate changeAtmospheric sciencesEcologyGeographyGeologyBiology

Abstract

fetched live from OpenAlex

Wetlands in the Qinghai-Tibet Plateau are a unique and fragile ecosystem undergoing rapid changes. We show two unique patterns of mercury (Hg) accumulation in wetland sediments. One is the 'surface peak' in monsoon-controlled regions and the other is the 'subsurface peak' in westerly-controlled regions. The former is attributed to the combined effects of increasing anthropogenic emissions and climate-induced changes in the cryosphere and wetland hydrology in the last 100-150 years. The climate changes in westerly-controlled regions in the last 50-70 years led to a fluctuation in hydrology and Hg peak in the sediment subsurface. The increase in legacy Hg input from soil erosion has largely enhanced the Hg accumulation rate in wetlands since the 1950s, especially in the proglacial wetlands. We highlight that accelerated glacier melting and permafrost thawing caused by global warming have altered geomorphology and hydrology, and affected Hg transport and accumulation in wetlands.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.168
Threshold uncertainty score0.217

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.049
GPT teacher head0.412
Teacher spread0.362 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it