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Record W7100507106

SHORT REPORT On reading colour rings

2015· article· en· W7100507106 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
Fundersnot available
KeywordsReading (process)White (mutation)EngravingCasualColor term
DOInot available

Abstract

fetched live from OpenAlex

The use of engraved plastic leg rings (Ogilvie 1972) has proved an extremely useful tool for long-term studies of individual birds within populations. Several studies have examined the longevity of marks (eg Rees et al 1990) and the colour fastness of certain materials (eg Lindsey et al 1995). In addition, Kania (2001) asked observers to read letters on metal rings used on White Stork Ciconia ciconia using binoculars. Inexperienced observers misread up to 27 % of letters, whereas trained observers misread up to 8 % of letters. On reading numbered neck collars on Canada Geese Branta canadensis, casual observers made 23 times more mistakes than trained professionals (Raveling et al 1990). However, as far as we are aware, there is little information on whether letters on certain colour combinations are easier to read than others. We examined this using a simple experimental approach using two different telescopes, sets of engraved plastic rings with different colour combinations and several observers. Each ‘ring ’ consisted of a plastic strip c 38 mm x 105 mm, the same dimensions as commonly used on Whooper Swan Cygnus cygnus colour rings. Three engraved letters, each 20 mm tall, 10 mm wide and with a 2 mm cut width were repeated three times on each ring. Each set of rings comprised five commonly used colour combinations; dark blue with white letters, orange/black, pale green/black, white/black and yellow/black. Each ring set, therefore, comprised 15 different letters. The letters were randomly chosen from 15 letters normally used on engraved rings

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)0.002
metaresearch head score (Gemma)0.008
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.224
Threshold uncertainty score0.748

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.000
Scholarly communication0.0010.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.2240.119

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 head0.035
GPT teacher head0.278
Teacher spread0.243 · 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
Published2015
Admission routes1
Has abstractyes

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