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Record W174052508

Peat as an Archive of Remote Mercury Deposition in the Hudson Bay Lowlands, Ontario, Canada

2014· article· en· W174052508 on OpenAlexaboutno aff
William James Goacher

Bibliographic record

VenueScholarship@Western (Western University) · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
Fundersnot available
KeywordsPeatBayMercury (programming language)Deposition (geology)BogOceanographyEnvironmental scienceGeologyArchaeologyGeographyGeomorphology
DOInot available

Abstract

fetched live from OpenAlex

Peat from the Hudson Bay Lowlands (HBL) in Northern Ontario, Canada was used to reconstruct historical accumulation of mercury (Hg) over more than 7000 years before present. Nine cores, many with previously published paleoclimate studies, were analyzed for Hg and accumulation rates were calculated. Anthropogenic Hg enrichment factors were calculated based on accumulation rates. A more exclusive calculation of the anthropogenic enrichment factor corroborates modelling efforts that have suggested re-cycling legacy Hg is a much greater contributor to present day deposition than previously thought, but not prior to ~500 cal yrs BP. An older pre-industrial record provides a better background accumulation rate than short cores.\nEnrichment factors were then compared across a latitudinal gradient. Enrichment factors decreased with latitude as well as distance from the James Bay. These spatial trends are attributed to differing halogen chemistry above the bay as well as distance from point sources of Hg.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.019
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.006
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.041
GPT teacher head0.264
Teacher spread0.223 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2014
Admission routes1
Has abstractyes

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