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Record W2778041851 · doi:10.5772/intechopen.69779

Genetic Characterization of Jaguars (Panthera onca) in Captivity in Zoological Parks of Colombia

2017· book-chapter· en· W2778041851 on OpenAlexfundno aff
Santiago Jiménez González, Manuel Ruiz‐García, Jesús E. Maldonado, Ligia Mercedes Jimenez, Alberto Sánchez, Tammy R. Wilbert, Susan L. Castro, Jimmy H. Vargas, Sonia Quintanilla, Haydy Monsalve, Claudia Jiménez Escobar

Bibliographic record

VenueInTech eBooks · 2017
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
FundersInstitute of GeneticsNational Cancer InstituteSmithsonian Institution
KeywordsJaguarInbreedingGenetic diversityPopulationZoologyCaptivityBiologyEffective population sizeKinshipGeographyEcologyDemography

Abstract

fetched live from OpenAlex

The construction of the pedigree of captive jaguars (Panthera onca) in zoological parks of Colombia was done using the analysis of the Regional Studbook for Jaguars and DNA analysis of 9 microsatellites of 20 Jaguars (n=20). The assignments for paternities and maternities were done with for the program CERVUS and the relationship between animals were established with the KINSHIP program. The analysis of the Studbook was done with SPARKS and PM2000 software generating the following values: genetic diversity for the population (GD=0.7832), potential genetic diversity (GD=0.9113), genic value (GV=0.7846), mean coefficient of inbreeding (F=0.0179), and the Mean KINSHIP (MK) for each individual. The averages of the observed and expected heterozygosity were 0.687 and 0.684 respectively. Nevertheless, a wild jaguar sample of 156 individuals obtained in Colombia substantially showed a higher degree of gene diversity (H = 0.87) than the Colombian captive jaguar population. Thus, the captive jaguar population retained 78 % of the gene diversity of the Colombian wild jaguar population. With this study the pedigree of the captive population of jaguars was built in order to develop an ex situ conservation plan for the species in the Colombian zoological parks.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.204
Threshold uncertainty score0.765

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.019
GPT teacher head0.225
Teacher spread0.205 · 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.

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

Citations3
Published2017
Admission routes1
Has abstractyes

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