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Record W1527952339 · doi:10.48044/jauf.2007.003

An Evaluation of Bur Oak (<i>Quercus macrocarpa</i>) Decline in the Urban Forest of Winnipeg, Manitoba, Canada

2007· article· en· W1527952339 on OpenAlexafffundabout
Haley A. Catton, Scott St. George, W. R. Remphrey

Bibliographic record

VenueArboriculture & Urban Forestry · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaManitoba Hydro
KeywordsAbiotic componentPopulationCrown (dentistry)DendrochronologyGeographyEcologyCompetition (biology)BiologyForestryDemographyArchaeology

Abstract

fetched live from OpenAlex

Abstract Winnipeg, Manitoba, Canada, has a large, indigenous population of bur oak ( Quercus macrocarpa Michx.). In the 1980s, many of these trees were showing signs of decline, a disease caused by a complex of abiotic and secondary biotic stressing agents. Potential causal factors were investigated by comparing various aspects of 120 bur oaks visually rated as healthy or declined based on crown dieback levels. The results indicated that many selected bur oak trees predated surrounding urban development and that declined trees were significantly older with more severe stem wounds and competition from surrounding trees than healthy specimens. Average annual growth ring widths of healthy and declined trees were similar in the early part of the 20th century. However, decline actually began decades before symptoms were noticed, coinciding with a period of intense city-wide urban development, as growth of declined trees was slower than that of healthy trees beginning sporadically in the 1940s and consistently from 1974 to 2001. During the early years of decline, the year-by-year separation in ring width between the two categories was significantly positively related to precipitation levels. This suggested that in wet years, declined trees may have been surrounded by unfavorable water-logged soils, possibly as a result of natural drainage patterns being impeded by urban development.

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)0.002
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 score0.461
Threshold uncertainty score0.583

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.016
GPT teacher head0.237
Teacher spread0.221 · 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

Citations19
Published2007
Admission routes3
Has abstractyes

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