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Record W4309564631 · doi:10.1038/s43247-022-00619-y

Root uptake dominates mercury accumulation in permafrost plants of Qinghai-Tibet Plateau

2022· article· en· W4309564631 on OpenAlex
Xun Wang, Wei Yuan, Che‐Jen Lin, Dingyong Wang, Ji Luo, Jicheng Xia, Wei Zhang, Fei Wang, Xinbin Feng

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

VenueCommunications Earth & Environment · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsUniversity of Manitoba
FundersChinese Academy of SciencesNational Natural Science Foundation of China
KeywordsPermafrostMercury (programming language)ArcticPlateau (mathematics)EcosystemPhysical geographyEnvironmental scienceEarth scienceArctic vegetationTerrestrial ecosystemEnvironmental chemistryGeologyEcologyTundraChemistryBiologyGeographyOceanography

Abstract

fetched live from OpenAlex

Abstract Uptake of atmospheric elemental mercury via foliage is thought to be the dominant pathway of mercury accumulation in terrestrial ecosystems, including those in the Arctic permafrost regions. Whether a similar process operates in alpine permafrost regions remains unknown. Here we report mercury concentrations and stable isotopic signatures in a large cluster alpine permafrost regions of mid-latitude Qinghai-Tibet Plateau. We find a transition from foliage to root uptake of mercury as elevation increases. In alpine permafrost regions, we find that root uptake of mercury from the surrounding soil is the dominant accumulation pathway. We estimate that root uptake accounts for 70 ± 19% of plant mercury in permafrost regions of the Qinghai-Tibet Plateau and propose that this may be related to the harsh climate conditions suppressing foliage growth and promoting lateral root growth.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.047
GPT teacher head0.289
Teacher spread0.243 · 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