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Record W2031123464 · doi:10.1139/z09-079

Failure to estimate reliable sex ratios of guanaco from road-survey data

2009· article· en· W2031123464 on OpenAlexvenueno aff
Julieta Pedrana, Alejandro Rodrı́guez, Javier Bustamante, Alejandro Travaini, Juan I. Zanón Martínez

Bibliographic record

VenueCanadian Journal of Zoology · 2009
Typearticle
Languageen
FieldPsychology
TopicPrimate Behavior and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsSex ratioBiologyJuvenileNull hypothesisPolygynyMammalUngulateDemographyAlternative hypothesisEcologyZoologyStatisticsHabitatMathematics

Abstract

fetched live from OpenAlex

The guanaco ( Lama guanicoe (Müller, 1776)) is a monomorphic polygynous mammal whose adult sex ratio is expected to be balanced or biased towards females. Remarkably male-biased sex ratios of adult guanacos are often estimated from road surveys. We analyzed the distribution of guanaco social groups recorded during road surveys in Patagonia, Argentina, to test the hypothesis that group assignation based upon behavioral traits is not unequivocal and can be biased by survey factors. Guanacos are organized into three social units (family groups, male groups, and solitary males) that are identified by their grouping behaviour. We recorded 992 guanaco groups, and estimated an adult sex ratio of 3.2 males/female. We used generalized additive models to test the null hypothesis that the probability of recording a group as a family group was constant. Alternatively, this probability could decrease when juvenile abundance and (or) detectability was low. The most parsimonious model showed that the probability of classifying a “family” group increased with date, and decreased with group size, distance to the observer, and time of day. Our results do not support the null hypothesis and suggest that road surveys are unsuitable to estimate reliably the social structure or sex ratio of guanaco populations.

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)0.006
metaresearch head score (Gemma)0.030
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 score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.030
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.054
GPT teacher head0.345
Teacher spread0.291 · 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

Citations8
Published2009
Admission routes1
Has abstractyes

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