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Record W7095160515

Asymmetry in antlers of barren-ground caribou

2016· article· en· W7095160515 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicJapanese History and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsAntlerDominance (genetics)HerdSame sexHolstein Cattle
DOInot available

Abstract

fetched live from OpenAlex

Abstract: Pairs of antlers were obtained from 287 barren-ground caribou (Rangifer tarandus groenlandicus) of the Kaminuriak herd in the Northwest Territories, Canada. The morphological dominance of the brow tines by antler pair was determined: 15.7 % were enlarged on the left; 14.6 % on the right; 14.6 % on both sides; and 55.1 % on neither side. N o evidence for a greater rate of occurrence of left or right dominance of the brow tine was obtained when considered by sex or age class (P>0.05). Antler pairs with both brow and bez tines present varied from 84.4 % for males with their 5th to 10th set of antlers; 39.3 % for males with their 2nd to 4th set; 21.2 % for females with their 5th to 16th set; and 6.3 % for females with their 1st to 4th set. Both brow and bez tines were present proportionately more often than expected on antler pairs from males compared to females regardless of age (P <0.005). Both brow and bez tines also were present proportionately more often than expected on antler pairs from males (P <0.005), females (P <0.01), or both sexes combined (P <0.01) with their 5th or later set than compared to when they had their 4th or earlier set.

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)0.001
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 score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0030.000

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 head0.017
GPT teacher head0.275
Teacher spread0.258 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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