MétaCan
Menu
Back to cohort
Record W2161538734 · doi:10.1017/s0952836904005606

Growth and variation in the bacula of polar bears (<i>Ursus maritimus</i>) in the Canadian Arctic

2004· article· en· W2161538734 on OpenAlexaffabout
Markus Dyck, Jackie M. Bourgeois, Edward H. Miller

Bibliographic record

VenueJournal of Zoology · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsMemorial University of NewfoundlandGovernment of Nunavut
Fundersnot available
KeywordsUrsus maritimusBiologyArcticSexual maturityUrsusCoefficient of variationVariation (astronomy)Animal sciencePolarZoologyGeographic variationEcologyAnatomyDemographyPopulationStatistics

Abstract

fetched live from OpenAlex

Abstract Structure and growth of the baculum (os penis) in arctoid carnivores have been well described for many species. This study presents the first extensive analysis of bacular growth and variation for bears (Ursidae), based on 871 bacula of polar bears Ursus maritimus (858 of known age) that were shot in the Canadian Arctic from 1994 to 1997. Bacular length, maximal diameter and mass increased from 109 mm, 5.93 mm and 2.68 g respectively in 1‐year‐old bears ( n = 34) to 190 (maximum 222) mm, 18.7 (24.4) mm, and 20.4 (31.9) g respectively in bears ≥ 10 years of age ( n &gt; 200). Bacular length is ˜8% of body length in adults. Bacula were moderately variable in size: coefficient of variation for length, diameter, and mass 1/3 were 5.2, 10.0 and 5.4% respectively (16.3% for mass). No geographic variation in size was apparent. Bacula reached asymptotic size at 8–9 years of age. At physiological sexual maturity (˜6 years of age), bacula were at 89, 73 and 62% of asymptotic length, diameter and mass respectively (compared with body length at ˜95%). Interpretation of these findings must await behavioural and physiological information on courtship and copulation in the polar bear, and comparative data on other ursids.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.384
Threshold uncertainty score0.914

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 head0.007
GPT teacher head0.200
Teacher spread0.193 · 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

Citations28
Published2004
Admission routes2
Has abstractyes

Explore more

Same venueJournal of ZoologySame topicWildlife Ecology and ConservationFrench-language works237,207