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Record W2340564981 · doi:10.1139/cjb-2015-0262

Sandhill Fen, an initial trial for wetland species assembly on in-pit substrates: lessons after three years

2016· article· en· W2340564981 on OpenAlexfundvenueaboutno aff
Dale H. Vitt, Melissa House, Jeremy A. Hartsock

Bibliographic record

VenueBotany · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsnot available
FundersSyncrude
KeywordsSandhillPeatEcologyWetlandPlant communityOrdinationMarshMireVegetation (pathology)Riparian zoneAbundance (ecology)HabitatBiologyVascular plantEnvironmental scienceSpecies richness

Abstract

fetched live from OpenAlex

Open-pit mining of oil sands removes wetland plant communities from the landscape. Sandhill Watershed, located on Syncrude Canada’s oil sands lease, is the first reclamation of a complex watershed that includes a 17 ha central wetland designed to develop into a rich fen. Here we sample the vegetation after three years. Of the 124 plant species recorded, 48% are peat-forming species, including 24 bryophyte species. We identified, using ordination techniques, four plant assemblages that vary in abundance of peat-forming plants. Each assemblage occurs in a spatially distinct area of Sandhill Fen, forming vegetation zones that are closely associated with height of water table. The plant assemblage distributed in the wettest areas has abundant marsh species. The assemblages in the driest areas of the fen have large numbers of upland and weed species and few species characteristic of fens. In between is a species assemblage with an abundance of species characteristic of natural peat-forming habitats. Two key findings are: water levels control spatial distributions of species assemblages, and non-peat-forming plant species are abundant and a concern for the establishment of peat-forming wetlands. Future designs should include plans for a number of interconnected site types such as marshes, fens, and riparian areas.

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)0.003
metaresearch head score (Gemma)0.005
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 score0.324
Threshold uncertainty score0.644

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.035
GPT teacher head0.283
Teacher spread0.248 · 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

Citations49
Published2016
Admission routes3
Has abstractyes

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