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Record W4362475887 · doi:10.24908/iqurcp16351

An Assessment of Phosphorus Fractions in the Canadian High Arctic Post-Permafrost Disturbances

2023· article· en· W4362475887 on OpenAlexaffvenueabout
Erjia Guan

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsQueen's University
Fundersnot available
KeywordsPermafrostChronosequencePhosphorusEnvironmental scienceArcticDisturbance (geology)Carbon cycleHydrology (agriculture)EcologySoil waterGeologyChemistrySoil scienceBiologyEcosystem

Abstract

fetched live from OpenAlex

Climate change is impacting all natural processes, and the phosphorus cycle is no exception. With the High Arctic warming at a significantly increased rate compared to the rest of the world, thawing permafrost could potentially release great amounts of carbon, which through cellular respiration in microbes and plants, would eventually enter the atmosphere creating a runaway positive feedback cycle. The purpose of this research is to determine the amounts of the different forms of phosphorus present in High Arctic soil after a permafrost disturbance. This project will be done as a chronosequence as opposed to a longitudinal study, as it is not practical to measure time over a period of 60-70 years. Soil samples were collected from the Cape Bounty Arctic Watershed Observatory on Melville Island in Canada. 3 sites were sampled, each with a different amount of time elapsed since a permafrost disturbance occurred. These 3 sites vary from the disturbance occurring 1-2 years ago, to 14 years ago, to 60-70 years ago. 3 replicates were taken from each site. Furthermore, each site had its own respective control, from which 3 replicates were also taken. Chemical analysis of the amount of phosphorus present in the soil samples will be done using the Hedley method of phosphorus fractionation. The Hedley method is a method of phosphorus fractionation that is done by sequentially adding stronger reagents to remove various forms of occluded, non-occluded, labile, and resistant forms of phosphorus. The results of this project are still unknown, as much lab work has yet to be completed. However, I expect phosphorus fractions results to vary between the different sites. This is significant as human disturbances and interference may cause accelerated permafrost thaw in the High Arctic, furthering altering ecosystems.

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 score0.030
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0040.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.117
GPT teacher head0.389
Teacher spread0.272 · 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
Published2023
Admission routes3
Has abstractyes

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