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Record W2010194551 · doi:10.1139/z02-183

Inbreeding, outbreeding, infant growth, and size dimorphism in captive Indian rhinoceros (<i>Rhinoceros unicornis</i>)

2002· article· en· W2010194551 on OpenAlexvenueno aff
Samuel Zschokke, Bruno Baur

Bibliographic record

VenueCanadian Journal of Zoology · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and phenotypic traits in livestock
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyInbreedingRhinocerosSexual dimorphismOutbreeding depressionZoologyPopulationOffspringGestation periodGestationDemographyPregnancyGenetics

Abstract

fetched live from OpenAlex

Effects of inbreeding and outbreeding on gestation period, birth mass, infant mortality, and growth, as well as the ontogeny of sexual size dimorphism, were analyzed in captive Indian rhinoceros (Rhinoceros unicornis L., 1758) using studbook data. Neither gestation period nor birth mass were affected by inbreeding. However, inbred calves grew slower and had a lower mortality rate than non-inbred ones. It is suggested that the severe bottleneck experienced in the early twentieth century by the Kaziranga population, from which most captive-born Indian rhinoceroses descend, resulted in strong inbreeding with consequent purging of recessive lethal alleles. Outbred individuals (offspring of matings between individuals from the Kaziranga and the Chitwan populations) had a higher infant mortality rate, suggesting that the two populations are genetically partially incompatible. Among captive individuals, adult males were found to be heavier (2300 kg) and larger (shoulder height = 172 cm) than females (1800 kg, 160 cm). There were, however, no sex differences in gestation period, birth mass, or infant growth. This suggests that sexual dimorphism in adults is the result of a longer growth period in males rather than a difference in growth rate between the sexes.

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 score0.016
Threshold uncertainty score0.032

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 head0.011
GPT teacher head0.197
Teacher spread0.186 · 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

Citations43
Published2002
Admission routes1
Has abstractyes

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