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Record W2160851305 · doi:10.1139/x01-026

Balsam fir self-thinning relationship and its constancy among different ecological regions

2001· article· en· W2160851305 on OpenAlexfundvenueaboutno aff
Eric Bégin, Jean Bégin, Louis Bélanger, Louis‐Paul Rivest, Stéphane Tremblay

Bibliographic record

VenueCanadian Journal of Forest Research · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsnot available
FundersUniversité Laval
KeywordsThinningBalsamAbies balsameaMathematicsEcologyJackknife resamplingBorealStatisticsForestryEnvironmental scienceGeographyBiologyBotany

Abstract

fetched live from OpenAlex

The constancy of balsam fir (Abies balsamea (L.) Mill.) self-thinning relationship has been investigated among four study areas located in different ecological regions of Quebec's humid boreal forest. These four study areas contained respectively 348, 252, 146, and 55 observations (plots × measures) sampled over a period of up to 40 years. A self-thinning fitting method was developed to position objectively the self-thinning lines but, moreover, to allow comparisons among the different study areas. This method relies on principal component analysis to estimate the self-thinning line parameters and on the "jackknife" procedure to provide a standard error of these estimates. Results demonstrate a concordance for the slope (p = 0.136) and the intercept (p = 0.148) among self-thinning relationships of those study areas. The combination of these four study areas in one large data set, to provide a general estimation of balsam fir self-thinning line, has given a slope of –1.441 with a 4.114 intercept which is in agreement with the –3/2 power law of self-thinning. In this study, this law was able to describe the size–density relationship of stands of various ages and growing within different conditions as expressed by the different ecological regions.

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 score0.260
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
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.054
GPT teacher head0.293
Teacher spread0.240 · 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

Citations49
Published2001
Admission routes3
Has abstractyes

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