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Record W2366689221 · doi:10.21068/bc.v16i2.379

Mammals of the Córdoba Department of Colombia: history and conservation status

2015· article· en· W2366689221 on OpenAlexaboutno aff
Javier Racero-Casarrubia, Jesus Ballesteros-Correa, Jairo Pérez‐Torres

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyConservation statusBiologyEcologyHabitat

Abstract

fetched live from OpenAlex

A taxonomic list of the mammals recorded from the department of Córdoba is presented with data from reference collections of national and foreign museums. We include research results from research groups at the Unicórdoba Biodiversity research center (University of Cordoba) and the Functional Ecology Laboratory (UNESIS- Pontificia Universidad Javeriana). Databases of 13 museums in North America (MaNIS) were reviewed. Besides the records found in the Smithsonian National Museum of Natural History (NMNH), Royal Ontario Museum (ROM), Texas Cooperative Wildlife Collection (TCWC) and USA Field Museum of Natural History (FMHN). Mammals of Córdoba department are represented by 40 families, 90 genera and 117 species. The greatest species richness of mammals was found in the subregions of upper Sinú and San Jorge. The greatest number of species are of the order Chiroptera (48.9 %), followed by Carnivora (12 %), Rodentia (10.3 %) and Cetacea (9.4 %).

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)0.001
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 score0.174
Threshold uncertainty score0.346

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.299
GPT teacher head0.461
Teacher spread0.161 · 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

Citations10
Published2015
Admission routes1
Has abstractyes

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