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Record W2130517555 · doi:10.14214/sf.46

From the Arctic Circle to the Canadian prairies – a case study of silver birch acclimation capacity

2012· article· en· W2130517555 on OpenAlexfundaboutno aff
Matti Rousi, Boy Possen, Risto Hagqvist, Barb R. Thomas

Bibliographic record

VenueSilva Fennica · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant responses to elevated CO2
Canadian institutionsnot available
FundersUniversity of AlbertaAlberta-Pacific Forest Industries
KeywordsAcclimatizationThe arcticArcticEnvironmental scienceGeographyForestryEcologyBiologyGeologyOceanography

Abstract

fetched live from OpenAlex

Earlier provenance research has indicated poor success even in short distance transfers (> 2–3° latitude) of silver birch (Betula pendula Roth) southward from their origin. These results may indicate poor adaptability of silver birch to a warming climate. Some of the scenarios for a warming climate in Finland suggest effective heat sums are likely to double in the north and increase 1.5 fold in the south for the period of 2070–2099. Consequently, the outlook for silver birch appears bleak. To study the acclimation of birch to this projected change we established a provenance trial in northeastern Alberta, Canada, at the temperature area currently predicted for Central Finland (lat. 64–66°N) at the turn of this century (1400 dd). Our 10-year experiment showed that all the Finnish provenances (origins 61–67°N) have acclimated well to the warmer growth conditions experienced in Alberta at 54°N. These results suggest that silver birch has the potential to acclimate to thermal conditions predicted for Finland at the end of the 21st century. Our results also indicate that silver birch has the potential as a plantation species in Canada, where the Finnish birch grew faster in the boreal forest region of Canada than local paper birch (Betula papyrifera Marsh.) provenances.

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)0.001
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 score0.016
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.047
GPT teacher head0.248
Teacher spread0.201 · 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

Citations15
Published2012
Admission routes2
Has abstractyes

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