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Record W2159677236 · doi:10.1080/jom.2007.9710848

Glacial geomorphology of the east-central Canadian Arctic

2007· article· en· W2159677236 on OpenAlexaboutno aff
Hernán De Angelis

Bibliographic record

VenueJournal of Maps · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
Fundersnot available
KeywordsMoraineGeologyLandformGlacial periodGlacierGlacial landformArcticIce sheetPhysical geographyGeomorphologyRemote sensingGeographyOceanography

Abstract

fetched live from OpenAlex

Please click here to download the map associated with this article. This article describes palaeoglaciological mapping of the portion of the Canadian Arctic formerly covered by the north-easternmost Laurentide Ice Sheet. The mapped area stretches between the meridians 106°W and 61°W, and the parallels 60°N and 75°N, embracing an area of 3.19 x 106 km2. The work was focused on determining the location of landforms that are required as input for a glaciological inversion model, i.e. glacial lineations, eskers, moraine ridges, ribbed moraine and De Geer moraines; and forms the basis of a reconstruction of the geometry and evolution of palaeo-ice streams in this portion of the Laurentide Ice Sheet. Emerged areas were mapped through the geomorphological interpretation of Landsat 7 Enhanced Thematic Mapper Plus (ETM+) satellite images. Information on striae and other minor indicators of glacial activity were extracted from maps and reports by the Geological Survey of Canada, published articles and, for a few locations, by the author's own observations. Information on landforms located on some submerged areas where extracted from publicly available sonar surveys. All data were digitally processed within a Geographical Information System and stored in a spatially enabled database. The results are presented as a printable map at 1:2,400,000 scale.

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)0.000
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 score0.013
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.007
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.224
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

Citations15
Published2007
Admission routes1
Has abstractyes

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