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Record W2120572074 · doi:10.1086/656285

First Assessment of Mountains on Northwestern Ellesmere Island, Nunavut, as Potential Astronomical Observing Sites

2010· article· en· W2120572074 on OpenAlexaffabout
Eric Steinbring, R. G. Carlberg, Bryce Croll, G. G. Fahlman, Paul Hickson, Liviu Ivănescu, Brian Leckie, Thomas Pfrommer, Matthias Schoeck

Bibliographic record

VenuePublications of the Astronomical Society of the Pacific · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversité de MontréalUniversity of British ColumbiaNational Research Council CanadaUniversity of TorontoHerzberg Institute of Astrophysics
Fundersnot available
KeywordsSkyArcticPermafrostThe arcticAutomatic weather stationGeologyPhysical geographyWind speedMeteorologyRemote sensingClimatologyOceanographyGeography

Abstract

fetched live from OpenAlex

Ellesmere Island, at the most northerly tip of Canada, possesses the highest mountain peaks within 10° of the pole. The highest is 2616 m, with many summits over 1000 m, high enough to place them above a stable low-elevation thermal inversion that persists through winter darkness. Our group has studied four mountains along the northwestern coast that have the additional benefit of smooth onshore airflow from the ice-locked Arctic Ocean. We deployed small robotic site-testing stations at three sites, the highest of which is over 1600 m and within 8° of the pole. Basic weather and sky-clarity data for over 3 yr beginning in 2006 are presented here and compared with available nearby sea-level data and one manned midelevation site. Our results point to coastal mountain sites experiencing good weather: low median wind speed, high clear-sky fraction, and the expectation of excellent seeing. Some practical aspects of access to these remote locations and operation and maintenance of equipment there are also discussed.

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 score0.468
Threshold uncertainty score0.941

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.222
Teacher spread0.209 · 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

Citations19
Published2010
Admission routes2
Has abstractyes

Explore more

Same venuePublications of the Astronomical Society of the PacificSame topicCryospheric studies and observationsFrench-language works237,207