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Record W7047481019

Frost hardiness of balsam poplar (Populus balsamifera L.) during the spring dehardening period / by Steven R. Watson

2017· other· en· W7047481019 on OpenAlexaboutno aff

Bibliographic record

VenueKnowledge Commons (Lakehead University) · 2017
Typeother
Languageen
FieldPhysics and Astronomy
TopicSuperconducting and THz Device Technology
Canadian institutionsnot available
Fundersnot available
KeywordsFrost (temperature)Hardiness (plants)CuttingPhenologyShootSpring (device)BalsamAnnual growth cycle of grapevinesRange (aeronautics)
DOInot available

Abstract

fetched live from OpenAlex

Changes in the frost hardiness of balsam poplar (Populus balsamifera L.) \ncuttings from four populations along a latitudinal transect from N. Wisconsin to \nBearskin L, Ontario, were examined during the spring of 1987. Hardiness levels of \ndormant stem cuttings from the two extreme populations were examined after \nvarious incubation periods, under two different dehardening temperature regimes, \nwith a standard freezing test (freezing temperatures: -S.-l 1 ,-19, and -27? C). \nNorthern clones were less susceptible to frost injury than southern clones during \nthe spring dehardening period, and this phenomenon was closely related to the \ntendency of northern clones to remain dormant longer than southern clones. High \nwithin-population variation was also noted in hardiness levels and bud break \ncharacteristics. Leaf tissue dehardened more rapidly than stem tissue, and the \ndehardening process occured more rapidly at the higher incubation temperature. \nA second study in which cuttings from the four provenances were subjected \nto a series of controlled freezing temperatures (-3,-6,-9,-12,-18, and -24? C) at \nparallel developmental stages revealed that provenance differences in frost injury \nwere essentially a function of differential shoot phenology at the time of freezing. \nCuttings were hardy to -18? C when leaf expansion first became visible, and could \nbe subjected to -12? C without injury when the newly expanding shoot became \nvisible, indicating that an attenuated form of hardiness may exist even when the \nshoots are actively growing.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.016
GPT teacher head0.231
Teacher spread0.215 · 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
Published2017
Admission routes1
Has abstractyes

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