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Record W6969535794 · doi:10.5683/sp3/j1vomq

Using marsh organs to test seed recruitment in tidal freshwater marshes

2022· dataset· en· W6969535794 on OpenAlexafffund

Bibliographic record

VenueBorealis · 2022
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMarshGerminationEstuaryElevation (ballistics)Salt marshMesocosm

Abstract

fetched live from OpenAlex

<b>Abstract</b><br/><p><strong>Premise:</strong> Seed recruitment niches along estuarine elevation gradients are seldom experimentally field-tested under tidal regimes of the Pacific Northwest of North America. Addressing this knowledge gap is important to better understand estuary restoration and plant community response to sea level rise.</p> <p><strong>Methods:</strong> Germination was tested in marsh organ mesocosms across an elevation gradient (0.5–1.7 m above mean sea level). Seeds were sown on sterile peat moss, and the tops of pipes were secured with horticultural “frost cloth” to ensure no experimental seeds were washed out and no new seeds were introduced. The trials tested artificial and overwinter chilling regimes, as well as the presence and/or absence of a near-neighbor transplant.</p> <p><strong>Results:</strong> <em>Carex</em> <em>lyngbyei</em> had significant elevation-driven germination after overwinter and artificial chilling. <em>Schoenoplectus tabernaemontani</em> had near-significant germination across elevation after overwinter chilling, and germination in the absence of competition was significantly greater than with a near-neighbor transplant.</p> <p><strong>Discussion:</strong> <em>Carex lyngbyei</em> had the highest germination rate at higher elevations, which suggests restricted seed recruitment potential, and required clonal expansion to extend into lower marsh elevations. Identifying species-specific recruitment niches provides insight for restoration opportunities or invasive species monitoring, as well as for estuary migration under sea level rise.</p>

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.338
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0220.001

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 head0.089
GPT teacher head0.328
Teacher spread0.238 · 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 designNot applicable
Domainnot available
GenreDataset

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
Published2022
Admission routes2
Has abstractyes

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Same venueBorealisFrench-language works237,207