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Record W2513482816

The biogeochemistry of a restoring macrotidal salt marsh : Cheverie Creek, Nova Scotia

2016· article· en· W2513482816 on OpenAlexaboutno aff
Christa Skinner

Bibliographic record

VenueSaint Mary's University Institutional Repository (Saint Mary's University) · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal wetland ecosystem dynamics
Canadian institutionsnot available
FundersU.S. Department of Transportation
KeywordsNova scotiaBiogeochemistrySalt marshOceanographyNova (rocket)GeologyHydrology (agriculture)Environmental scienceEngineering
DOInot available

Abstract

fetched live from OpenAlex

The biogeochemistry of a restoring macrotidal salt marsh: Cheverie Creek, Nova Scotia By: Christa Skinner Vegetation, hydrology, sediment characteristics, and soil chemistry were studied at Cheverie Creek Salt Marsh Restoration Site, NS.Sampling was conducted during the spring and summer months of 2014 to determine how hypertidal minerogenic salt marshes influence aboveground biomass production over the growing season.Aboveground biomass, sulfide concentration, salinity, and redox potential measurements were taken at each sampling location approximately every 2 weeks throughout the growing season.Sediment cores were taken once at each location to determine bulk density, organic matter, water content and grain size.Inundation frequency and duration were determined throughout the sampling period.Hydrology measured by water level recorders was found to influence salinity and redox potential, whereas sulfide concentration increased throughout the growing season.Sediment characteristics and soil chemistry were found to influence aboveground biomass production throughout the growing season.Areas surrounding pannes were associated with low aboveground biomass, highest salinity, high sulfide and low redox potential.April 1, 2016 I would like to thank my supervisor, Dr. Danika van Proosdij for taking me on as a student, sticking with me when one life event led into another, and allowing me to take charge of my project.Without her support and guidance, I would never have been able to take this project from thought through to completion.Thank you to the other members of

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 score0.171
Threshold uncertainty score0.344

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.166
Teacher spread0.160 · 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
Published2016
Admission routes1
Has abstractyes

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