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Record W2297034437 · doi:10.15273/pnsis.v44i1.3883

WOODVILLE ICE CAVE (HANTS COUNTY, NOVA SCOTIA) AND NOTES ON THE ‘ICE CAVES’ OF THE MARITIME PROVINCES

2007· article· fr· W2297034437 on OpenAlexaffvenueabout
Max Moseley

Bibliographic record

VenueProceedings of the Nova Scotian Institute of Science · 2007
Typearticle
Languagefr
FieldEarth and Planetary Sciences
TopicSubterranean biodiversity and taxonomy
Canadian institutionsNova Scotia Hospital
Fundersnot available
KeywordsCaveNova scotiaKarstArchaeologyGeologyHumanitiesGeographyArt

Abstract

fetched live from OpenAlex

Several caves and sinkholes where snow and ice persist well into the summer exist in Nova Scotia and New Brunswick. In the past they were sometimes used as a source of ice or for cold storage, and are known locally as ‘ice caves’ or ‘ice holes’. Although they are not true ice caves in the speleological sense of the term because they do not contain perennial ice, they are very similar. Woodville Ice Cave in Hants County, Nova Scotia, described here, is a particularly good example. Invertebrates and bats recorded from such sites are briefly discussed and the possibility of finding psychrophilic fauna in them is suggested.Plusieurs grottes et dolines sont présentes là où la neige et la glace ne disparaissent que tard durant l’été en Nouvelle‑Écosse et au Nouveau-Brunswick. Autrefois, elles étaient parfois utilisées comme sources de glace ou aux fins d’entreposage sous froid. À l’échelle locale, elles sont connues sous le nom de glacières ou de puits de neige. Elles ne sont pas de véritables glacières au sens habituel dans le domaine de la spéléologie parce qu’elles ne contiennent pas de glace pérenne, mais elles sont très semblables. La grotte Woodville (Woodville Ice Cave) dans le comté de Hants (N.-É.) décrite dans leprésent document, est un très bon exemple. Nous discutons brièvement des invertébrés et des chauves‑souris observés dans de telles grottes et dolines, et nous suggérons qu’il est peut-être possible d’y observer des organismes psychrophiles.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.185
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.016
Scholarly communication0.0000.001
Open science0.0030.000
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 head0.053
GPT teacher head0.223
Teacher spread0.171 · 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

Citations1
Published2007
Admission routes3
Has abstractyes

Explore more

Same venueProceedings of the Nova Scotian Institute of ScienceSame topicSubterranean biodiversity and taxonomyFrench-language works237,207