MétaCan
Menu
Back to cohort
Record W2089811232 · doi:10.2166/nh.2007.006

Fluxes of As, Cu, Hg, Pb in lake sediments in the Coppermine River basin, Canada

2007· article· en· W2089811232 on OpenAlexafffundabout
Liisa Peramaki, Michael Stone

Bibliographic record

VenueHydrology research · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsUniversity of WaterlooFisheries and Oceans Canada
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSedimentSedimentationHydrology (agriculture)Structural basinEnvironmental scienceDrainage basinDeposition (geology)Trace metalGeologyTrace elementPhysical geographyGeochemistryMetalGeomorphologyGeographyChemistry

Abstract

fetched live from OpenAlex

Many watersheds in northern Canada are experiencing increasing pressures from resource extraction, development and the long-range transport of atmospheric pollutants. This study examines sediment accumulation and the spatial and temporal distribution of trace metals in bottom sediment of down gradient lakes in the headwaters of the Coppermine River basin, Canada. Sediment cores were collected from Lac de Gras, Desteffany Lake, Point Lake and Daring Lake using a plastic lined K–B single-gravity corer. Each core was dated using 210Pb and concentrations of trace metals (As, Cu, Hg, Pb) were determined in core sections. Sedimentation rates ranged from 101 g m−2 yr−1 at Desteffany Lake to 156 g m−2 yr−1 at Daring Lake and are comparable to other northern lakes. Concentrations of As and Cu were significantly higher at Lac de Gras. Metal loading data and enrichment ratios show that concentrations of Pb and Hg are elevated compared to historic background levels. Metal enrichment is from anthropogenic activities and atmospheric inputs. Lake sediment represents a good indicator of state for the Coppermine basin and documents historic trends of metal deposition. However, the indicator has low sensitivity to change and coarse temporal resolution due to low sedimentation rates in northern environments.

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 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)0.006
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 score0.521
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.031
GPT teacher head0.332
Teacher spread0.301 · 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 teacher head, not a consensus.

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

Citations1
Published2007
Admission routes3
Has abstractyes

Explore more

Same venueHydrology researchSame topicHeavy metals in environmentFrench-language works237,207