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Record W7117493603 · doi:10.3398/064.085.0307

Describing a Gambel Oak / Douglas-Fir Community in Central Utah, USA

2025· article· W7117493603 on OpenAlexaff
Andrew Orlemann

Bibliographic record

VenueWestern North American Naturalist · 2025
Typearticle
Language
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsPricewaterhouseCoopers (Canada)
Fundersnot available
KeywordsChorologyEthnic communityEcological succession

Abstract

fetched live from OpenAlex

En este artículo se describe una comunidad de robles de Gambel y abetos de Douglas en el bosque nacional Manti–La Sal, en el centro de Utah (Estados Unidos). El sitio experimentó un evento de alteración que reemplazó a la masa forestal alrededor de 1856 y posteriormente fue quemado parcialmente por el incendio Seeley de 2012. Estos dos eventos, uno que probablemente restableció el sistema forestal y otro que dividió el sitio en dos condiciones (quemado y no quemado) brindaron la oportunidad de aprender más sobre la sucesión forestal, los regímenes de incendios y las interacciones de las especies en este tipo de vegetación. Los datos recopilados sugieren que este tipo de vegetación puede experimentar un régimen de incendios de alta severidad y baja frecuencia en el que las especies que brotan, principalmente robles, pero también álamos y arces, ocupan el sitio inmediatamente después de una perturbación. Con el tiempo, los abetos de Douglas pueden germinar y establecerse en la semisombra de estas especies caducifolias, y eventualmente convertirse en la especie de árbol/arbusto dominante, hasta que el próximo evento restablezca la trayectoria sucesional del área.

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 score0.176
Threshold uncertainty score0.351

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.017
GPT teacher head0.249
Teacher spread0.232 · 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
Published2025
Admission routes1
Has abstractyes

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