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Record W2805419169 · doi:10.1002/eco.1995

Nutrient supply rates in a boreal extreme‐rich fen using ion exchange membranes

2018· article· en· W2805419169 on OpenAlexfundaboutno aff
Jeremy A. Hartsock, E. Bremer

Bibliographic record

VenueEcohydrology · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsnot available
FundersSyncrude
KeywordsNutrientWetlandEnvironmental scienceBorealEnvironmental chemistryHydrology (agriculture)Hydraulic conductivityChemistrySoil scienceGeologyEcologySoil waterBiology

Abstract

fetched live from OpenAlex

Abstract Plant Root Simulator (PRS®) probes have been widely used to assess soil nutrients in the Athabasca Oil Sands Region of northern Alberta, Canada, but their optimum method of use and functionality in natural boreal fens and reclaimed wetlands needs to be determined. A PRS probe consists of an anion or cation exchange resin membrane that is housed in a plastic support. We assessed nutrient adsorption by PRS probes over three incubation periods (2, 24, and 384 hr) in a boreal extreme‐rich fen, a system with moderately high pore water electrical conductivity and a peatland site type that has been targeted in oil sand wetland reclamation. Ion adsorption by PRS probes was similar at 24 and 384 hr for ammonium, nitrate, phosphate, calcium, and magnesium, indicating that a stable or dynamic equilibrium was reached. However, potassium declined from 24 to 384 hr, likely due to displacement by more strongly held cations, while iron and manganese increased, likely due to increasingly anaerobic conditions. The finding that most nutrients were close to equilibrium on PRS probes within 24 hr has important implications for implementation and interpretation of PRS probe data in wetlands with moderately high pore water electrical conductivity.

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)0.000
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 score0.156
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

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)0.0030.000

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 head0.021
GPT teacher head0.249
Teacher spread0.228 · 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

Citations6
Published2018
Admission routes2
Has abstractyes

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