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Moss Diversity of a Pine-Oak Forest in Oaxaca, Mexico

2021· article· en· W3214990754 on OpenAlexaff
Enrique Hernández-Rodríguez, Eduardo Mendoza, Nicole J. Fenton, Paola Peña-Retes

Bibliographic record

VenueCryptogamie Bryologie · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLichen and fungal ecology
Canadian institutionsUniversité du Québec en Abitibi-Témiscamingue
Fundersnot available
KeywordsSpecies richnessMossFloristicsGeographyEcologyHerbariumFlora (microbiology)Species diversityAlpha diversityVegetation (pathology)Gamma diversityForestryBiology

Abstract

fetched live from OpenAlex

The pine-oak forests of Mexico are reservoirs of high biological diversity, largely due to their high richness of vascular flora. However, mosses have received little attention. We studied the floristic composition, diversity, and species richness of the moss community in the pine-oak forests of the Sierra Norte of Oaxaca, Mexico. A comprehensive list of the species occurring in the region was made by reviewing herbarium databases and conducting fieldwork. We analyzed alpha and beta diversity, as well as community structure, based on 60 sampling sites. Our results show the occurrence of 339 species of mosses in the study area, distributed in 168 genera and 52 families. We found high α and β diversity values compared with other vegetation types in Mexico. Our study provides a more detailed portrait of the high moss diversity occurring in the region.

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 score0.266
Threshold uncertainty score0.528

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 studies0.0010.000
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 head0.037
GPT teacher head0.233
Teacher spread0.196 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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