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Record W6925091966 · doi:10.1594/pangaea.811359

(Table 1) Effects of experimental warming on plant cover and diversity indices in an evergreen shrub at Alexandra Fiord

2010· dataset· en· W6925091966 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2010
Typedataset
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsEvergreenShrubPlant coverVegetation (pathology)Climate changePlant communityVascular plantAbundance (ecology)Sphagnum

Abstract

fetched live from OpenAlex

1. Identifying plant communities that are resistant to climate change will be critical for developing accurate, wide-scale vegetation change predictions. Most northern plant communities, especially tundra, have shown strong responses to experimental and observed warming.2. Experimental warming is a key tool for understanding vegetation responses to climate change. We used open-top chambers to passively warm an evergreen-shrub heath by 1.0-1.3 °C for 15 years at Alexandra Fiord, Nunavut, Canada (79 °N). In 1996, 2000 and 2007, we measured height, plant composition and abundance with a point-intercept method.3. Experimental warming did not strongly affect vascular plant cover, canopy height or species diversity, but it did increase bryophyte cover by 6.3% and decrease lichen cover by 3.5%. Temporal changes in plant cover were more frequent and of greater magnitude than changes due to experimental warming.4. Synthesis. This evergreen-shrub heath continues to exhibit community-level resistance to long-term experimental warming, in contrast to most Arctic plant communities. Our findings support the view that only substantial climatic changes will alter unproductive 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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.199
Threshold uncertainty score0.395

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0100.004

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 head0.028
GPT teacher head0.275
Teacher spread0.248 · 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 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
Published2010
Admission routes1
Has abstractyes

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