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Record W2000012427 · doi:10.1136/bjo.2005.074336

An icy stare

2005· article· en· W2000012427 on OpenAlexaboutno aff
Ivan R. Schwab

Bibliographic record

VenueBritish Journal of Ophthalmology · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsnot available
Fundersnot available
KeywordsCreaturesArcticThe arcticTree frogRange (aeronautics)OceanographyPaleontologyGeology

Abstract

fetched live from OpenAlex

Polar latitudes have among the harshest of climates on earth, and those ill prepared for these extremes sometimes pay with their lives. Witness those who were bent on finding the northwest passage in the early 1800s. Explorers such as Parry and Franklin, among others, lost ships, supplies, men, and in some cases their own lives in their quest for a route to the orient. They simply weren’t well enough prepared. Surprisingly, some vertebrates prepare for such extreme conditions in a manner many would consider wholly inconsistent with life. These creatures allow up to 65% of their body water, including their eyes, to freeze over winter! Rana sylvatica , the North American wood frog, pictured on the front cover, is found across most of the northern tier of North America. While the range of this frog does extend south of Canada into the northeast United States and even further south into northern Georgia, its stronghold is the Canadian shield, extending northwest to include Alaska. It is the only frog found north of the Arctic Circle. This ectothermic anuran survives there—a feat that …

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.282
Threshold uncertainty score0.747

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.2540.001

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 head0.025
GPT teacher head0.286
Teacher spread0.261 · 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.

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
Published2005
Admission routes1
Has abstractyes

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Same venueBritish Journal of OphthalmologySame topicSpecies Distribution and Climate ChangeFrench-language works237,207