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Record W4378212872 · doi:10.1139/cjss-2022-0129

Growth and survival of native wetland species in shallow capped centrifuged tailings and co-mixed tailings: a meso-scale greenhouse study

2023· article· en· W4378212872 on OpenAlexafffundvenue
Dani Degenhardt, Angeline Van Dongen, Jessica J. Hudson, Nicholas Utting, Stefan G. Schreiber

Bibliographic record

VenueCanadian Journal of Soil Science · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsNatural Resources CanadaCanadian Forest Service
FundersOffice of Energy Research and DevelopmentNatural Resources CanadaSyncrude
KeywordsTailingsLand reclamationEnvironmental scienceSubsoilPeatWetlandBiomass (ecology)RevegetationAgronomySoil scienceSoil waterEcologyChemistryBiology

Abstract

fetched live from OpenAlex

This 3-year meso-scale greenhouse study used 55-gallon columns to evaluate the survival and growth of boreal wetland communities planted on centrifuge (CF) tailings and co-mixed (CM) tailings capped with different reclamation cover soil capping designs. The CF tailings were capped with a shallow layer (10 and 30 cm) of peat reclamation material (PRM) and the CM tailings were capped with a shallow layer (5 cm) of PRM above 15 or 35 cm of reclamation subsoil (till). After 3 years, plant survival and growth on CF tailings showed significant improvement with a 10 cm PRM cap compared to the uncapped tailings, and plants growing on a 30 cm PRM cap outperformed those on the 10 cm PRM cap. Plant growth on CM tailings was significantly improved with a soil cover containing 5 cm PRM and at least 15 cm till. Among the seven native wetland species included in this study, the top performing species in terms of survival and above-ground biomass were Salix bebbiana, Scirpus microcarpus, and Carex aquatilis.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

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)0.0000.000

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 head0.013
GPT teacher head0.227
Teacher spread0.214 · 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 designBench or experimental
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

Citations7
Published2023
Admission routes3
Has abstractyes

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Same venueCanadian Journal of Soil ScienceSame topicPeatlands and Wetlands EcologyFrench-language works237,207