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Record W2182097839 · doi:10.82308/33091

Nested patterns of beta-diversity in forest Diptera

2010· article· en· W2182097839 on OpenAlexaboutno aff
Valerie Levesque‐Beaudin

Bibliographic record

VenueeScholarship@McGill (McGill) · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsnot available
Fundersnot available
KeywordsBeta diversityGeographyEcologyDiversity (politics)NestednessBiologyBiodiversitySociology

Abstract

fetched live from OpenAlex

Les patrons de diversité emboitée sur les diptères (Schizophora) de forêt tempérée ont été obtenus en déterminant l'échelle contribuant le plus à la diversité. Le terrain a été effectué (juin-juillet 2008) dans trois fragments forestiers du sud-ouest du Québec, utilisant trois échelles spatiales (arbre, parcelle, site). La diversité des diptères (239 espèces) et la composition en espèces n'était pas aléatoire à toutes les échelles. Ces échelles n'étaient pas également importantes pour les différents groups. Les plus petites échelles semblent structurer davantage la composition en espèces des diptères, ainsi que des deux groupes taxonomiques : Calyptratae et Acalyptratae. Les espèces communes étaient aussi principalement influencées par les petites échelles, alors que les espèces rares étaient davantage importantes à de plus larges échelles. L'échelle contribuant le plus à la diversité du pool était beta1 (entre les arbres). Les variables environnementales supportaient faiblement la composition en espèces.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.056
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.042
GPT teacher head0.204
Teacher spread0.162 · 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 source (direct Gemma or distilled Codex), 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
Published2010
Admission routes1
Has abstractyes

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