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Record W6959895963 · doi:10.11575/prism/25724

Dissolved Organic Carbon Dynamics in Constructed and Natural Fens in Athabasca Oil Sands Development Region near Fort McMurray, Alberta

2014· other· en· W6959895963 on OpenAlexaboutno aff

Bibliographic record

VenuePRISM (University of Calgary) · 2014
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Mapping and Diversity in Plants and Animals
Canadian institutionsnot available
Fundersnot available
KeywordsOil sandsDissolved organic carbonLand reclamationNatural (archaeology)Vegetation (pathology)PeatHydrology (agriculture)

Abstract

fetched live from OpenAlex

Peatlands, mainly fens, are largely disturbed in order to recover bitumen below the surface in the Athabasca oil sands development region, Alberta. Mine closure plans require ecosystem reclamation: hence fen construction method is being investigated. In this study, dissolved organic carbon (DOC) dynamics in a constructed fen were compared with three other diverse natural fens in the region. The constructed fen had lower soil DOC concentration than all natural fens. Based on E2/E3, E4/E6 and SUVA254 of the DOC, the constructed fen had DOC with significantly greater humic content, aromatic nature and larger molecular size than the natural fens. A laboratory DOC production study revealed that these patterns are likely due to the limited DOC contribution from newly planted vegetation at the constructed fen resulting in DOC largely derived from humified peat. These preliminary results suggest that DOC dynamics in the constructed system could be useful for evaluating reclamation success through time.

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 score0.088
Threshold uncertainty score0.177

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 studies0.0010.001
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 head0.004
GPT teacher head0.167
Teacher spread0.163 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

Explore more

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