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Record W2625750756 · doi:10.1002/etc.3886

Open-water and under-ice seasonal variations in trace element content and physicochemical associations in fluvial bed sediment

2017· article· en· W2625750756 on OpenAlexaffabout
Lorne E. Doig, Meghan Carr, Anna G.N. Meissner, Timothy D. Jardine, Paul D. Jones, Lalita Bharadwaj, Karl‐Erich Lindenschmidt

Bibliographic record

VenueEnvironmental Toxicology and Chemistry · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsSaskatchewan Health AuthorityGlobal Institute for Water SecurityUniversity of Saskatchewan
Fundersnot available
KeywordsTrace elementSedimentHydrology (agriculture)FluvialEnvironmental scienceGeologySedimentary depositional environmentSTREAMSGeomorphologyGeochemistry

Abstract

fetched live from OpenAlex

Across the circumpolar world, intensive anthropogenic activities in the southern reaches of many large, northward-flowing rivers can cause sediment contamination in the downstream depositional environment. The influence of ice cover on concentrations of inorganic contaminants in bed sediment (i.e., sediment quality) is unknown in these rivers, where winter is the dominant season. A geomorphic response unit approach was used to select hydraulically diverse sampling sites across a northern test-case system, the Slave River and delta (Northwest Territories, Canada). Surface sediment samples (top 1 cm) were collected from 6 predefined geomorphic response units (12 sites) to assess the relationships between bed sediment physicochemistry (particle size distribution and total organic carbon content) and trace element content (mercury and 18 other trace elements) during open-water conditions. A subset of sites was resampled under-ice to assess the influence of season on these relationships and on total trace element content. Concentrations of the majority of trace elements were strongly correlated with percent fines and proxies for grain size (aluminum and iron), with similar trace element grain size/grain size proxy relationships between seasons. However, finer materials were deposited under ice with associated increases in sediment total organic carbon content and the concentrations of most trace elements investigated. The geomorphic response unit approach was effective at identifying diverse hydrological environments for sampling prior to field operations. Our data demonstrate the need for under-ice sampling to confirm year-round consistency in trace element-geochemical relationships in fluvial systems and to define the upper extremes of these relationships. Whether contaminated or not, under-ice bed sediment can represent a "worst-case" scenario in terms of trace element concentrations and exposure for sediment-associated organisms in northern fluvial systems. Environ Toxicol Chem 2017;36:2916-2924. © 2017 SETAC.

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)0.000
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 score0.169
Threshold uncertainty score0.337

Distilled classifier scores by category (both heads)

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

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 head0.023
GPT teacher head0.260
Teacher spread0.238 · 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

Citations4
Published2017
Admission routes2
Has abstractyes

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