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Record W1953985436 · doi:10.21273/hortsci.41.6.1416

Morphology, Physiology, Survival, and Field Performance of Containerized Coastal Douglas Fir Seedlings Given Different Dormancy-induction Regimes

2006· article· en· W1953985436 on OpenAlexaff
Joanne E. MacDonald, John N. Owens

Bibliographic record

VenueHortScience · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicSeedling growth and survival studies
Canadian institutionsUniversity of VictoriaNatural Resources CanadaCanadian Forest Service
Fundersnot available
KeywordsSeedlingDormancyDry weightShootBiologyGrowing seasonHorticultureCollarDouglas firBotanyMoisture stressGerminationMoistureChemistry

Abstract

fetched live from OpenAlex

The effects of different dormancy-induction regimes on first-year containerized coastal Douglas fir [ Pseudotsuga menziesii (Mirb.) Franco var. menziesii ] seedling morphology and physiology in the nursery, as well as seedling survival and performance after one growing season in a common garden, were investigated. In early July, three dormancy-induction regimes were applied: moderate moisture stress (MS), short day (SD), and short day with moderate moisture stress (SD+MS). In early October, seedling height, root collar diameter, and shoot dry weight were unaffected by regime, but root dry weight was reduced in seedlings from the MS and SD+MS regimes compared with the SD regime. At this time, morphogenesis was completed in all terminal buds of seedlings from both SD regimes, whereas it continued in all terminal buds of seedlings from the MS regime. Furthermore, 25% to 88% of terminal buds from the SD regimes were endodormant, but none from the MS regime were endodormant. In March, budbreak occurred at the same time in seedlings from the two SD regimes and was earlier than in seedlings from the MS regime; root growth capacity was unaffected by regime. After one growing season, there were no regime differences in seedling survival, root collar diameter, shoot dry weight, root dry weight, length of the current-year leader, or number of needles on the leader.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.223
Threshold uncertainty score0.538

Codex and Gemma teacher scores by category

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

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 head0.010
GPT teacher head0.209
Teacher spread0.199 · 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.

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

Citations6
Published2006
Admission routes1
Has abstractyes

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