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A Quantitative Definition of Light Rings in Black Spruce ( <i>Picea mariana</i> ) at the Arctic Treeline in Northern Québec, Canada

2000· article· en· W2037780565 on OpenAlexaffabout
Lily Wang, Serge Payette, Yves Bégin

Bibliographic record

VenueArctic Antarctic and Alpine Research · 2000
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsUniversité LavalCenter for Northern Studies
Fundersnot available
KeywordsBlack spruceDendrochronologyThe arcticArcticRing (chemistry)ChronologyAtmospheric sciencesPicea abiesPhysical geographyGeologyBiologyPaleontologyTaigaEcologyGeographyChemistryOceanography

Abstract

fetched live from OpenAlex

Light rings in black spruce (Picea mariana [Mill.] BSP.) at the arctic treeline are characterized by pale-colored latewood made of a single or very few latewood-cell layers with thin-walled cells. Their widespread occurrence and their high frequency greatly facilitate the cross-dating procedure in dendrochronological studies. In this study, black spruce tree-ring density and wood structure were analyzed for light ring characteristics along with the mechanism of their formation according to ambient temperature. Light rings were quantitatively categorized into three classes based on the maximum tree-ring density using a normalized standard distribution. A light-ring chronology was established according to this classification. The results indicate that the grade of light ring was positively related to the frequency of light rings obtained from visual light-ring chronologies. The following anatomic variables were examined: number of cell layers of latewood, number of cells of the whole ring, percentage of latewood in the total ring width, and mean latewood cell-wall thickness. Among these anatomic variables, the mean latewood cell-wall thickness represents the best quantitative descriptor of a typical light ring as recognized by optical examination. The main causal factors of light rings are insufficient length of the growing season or cool summers.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.034
GPT teacher head0.271
Teacher spread0.237 · 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.

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

Citations27
Published2000
Admission routes2
Has abstractyes

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