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Record W2102166273 · doi:10.1071/zo09092

The genetic mating system, male reproductive success and lack of selection on male traits in the greater bilby

2010· article· en· W2102166273 on OpenAlexaff
Emily Miller, Mark D. B. Eldridge, Neil Thomas, Nicola Marlow, Catherine A. Herbert

Bibliographic record

VenueAustralian Journal of Zoology · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsDepartment of Environment and Conservation
Fundersnot available
KeywordsBandicootBiologyMating systemMatingZoologySirePopulationOffspringReproductive successEcologyCaptive breedingEvolutionary biologyMarsupialDemographyGeneticsHabitatEndangered species

Abstract

fetched live from OpenAlex

The greater bilby (Macrotis lagotis) is the sole remaining species of desert bandicoot on the Australian mainland. The mating system of this species remains poorly understood, due to the bilby’s cryptic nature. We investigated the genetic mating system of the greater bilby in a five-year study of a semi-free-ranging captive population that simulated their wild environment. Morphological traits were examined to determine whether these influenced patterns of male reproductive success and whether selection was acting on them. In any given year more than half the males (59.2 ± 9.3%) failed to sire any offspring. Approximately 70% of sires fathered one offspring, and 30% two or three offspring. Since paternity was not dominated by few males, and given the species’ solitary nature, lack of territoriality and large home ranges, it is likely that males adopt a roving strategy to find receptive females. These results are consistent with an overlap promiscuous mating system. Sires and non-sires could not be distinguished by their morphological traits, and there was no evidence for strong linear or non-linear selection on male traits. These data increase our understanding of bandicoot life-history traits and will assist conservation and management efforts.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.515
Threshold uncertainty score0.124

Codex and Gemma teacher scores by category

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

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 head0.045
GPT teacher head0.276
Teacher spread0.231 · 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

Citations13
Published2010
Admission routes1
Has abstractyes

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