MétaCan
Menu
Back to cohort
Record W6981728006

An Explorative Study of the Methods used in Dendrochronology and its Applications

2022· article· en· W6981728006 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell Image Analysis Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsPicea abiesDendrochronologySaccharumSilvicultureAceraceaeCoringWoody plantAnnual growth %
DOInot available

Abstract

fetched live from OpenAlex

The science of dendrochronology involves the dating of tree rings and analysis of their annual growth rates. It is important to conduct field studies to determine what tree species in a given area are suitable for analysis. This project began by coring Acer plantanoides, Acer saccharinum, Acer saccharum, and Picea abies from the Fanshawe Conservation Area in London, Ontario. Each core was prepped using standard procedures and analyzed for the visibility of annual rings. The tree rings of Acer plantanoides and Acer saccharinum were inadequate for accurate dating, and thus, only Acer saccharum and Picea abies were used and included in this poster. Ring widths of Acer saccharum and Picea abies were measured using WinDENDRO™ and COFECHA was used to evaluate the correlations of annual ring widths across the cores of each species. The intercorrelations of Acer saccharum were 0.404 and 0.571 for Picea abies. A standardized chronology was created by ARSTAN to analyze and compare annual growth rates across both species. Acer Saccharum and Picea abies both differed in their annual growth rates and degree of variability. Acer Saccharum had lower annual variation and overall lower annual growth rates than Picea abies. This project can be further expanded upon to include climate correlations in an attempt to explain the difference in growth rates and variability.

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 score0.091
Threshold uncertainty score0.546

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.079
GPT teacher head0.383
Teacher spread0.303 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueScholarship@Western (Western University)Same topicCell Image Analysis TechniquesFrench-language works237,207