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Record W6959248044 · doi:10.1021/acs.est.8b01680.s001

Total\nMercury and Methylmercury in Lake Water of Canada’s\nOil Sands Region

2018· article· en· W6959248044 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFigshare · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotanical Studies and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsMercury (programming language)MethylmercuryOil sandsWatershedDeposition (geology)Hydrology (agriculture)Water qualityTaiga

Abstract

fetched live from OpenAlex

Increased\ndelivery of mercury to ecosystems is a common consequence\nof industrialization, including in the Athabasca Oil Sands Region\n(AOSR) of Canada. Atmospheric mercury deposition has been studied\npreviously in the AOSR; however, less is known about the impact of\nregional industry on toxic methylmercury (MeHg) concentrations in\nlake ecosystems. We measured total mercury (THg) and MeHg concentrations\nfor five years from 50 lakes throughout the AOSR. Mean lake water\nconcentrations of THg (0.4–5.3 ng L<sup>–1</sup>) and\nMeHg (0.01–0.34 ng L<sup>–1</sup>) were similar to those\nof other boreal lakes and <5% of all samples exceeded Provincial\nwater quality guidelines. Lakes with the highest THg concentrations\nwere found >100 km northwest of oil sands mines and received runoff\nfrom geological formations high in metals concentrations. MeHg concentrations\nwere highest in those lakes, and in smaller productive lakes closer\nto oil sands mines. Simulated annual average direct deposition of\nTHg to sampled lakes using an atmospheric chemical transport model\nshowed <2% of all mercury deposited to sampled lakes was emitted\nfrom oil sands activities. Consequently, spatial patterns of mercury\nin AOSR lakes were likely most influenced by watershed and lake conditions,\nthough mercury concentrations in these lakes may be perturbed with\nfuture development and climatic change.

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.716
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0160.000

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 head0.024
GPT teacher head0.203
Teacher spread0.179 · 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