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Record W1833359074 · doi:10.7202/005654ar

The Omar Story: The Role of Omars in Assessing Glacial History of West-Central North America

2002· article· en· W1833359074 on OpenAlexaffvenueabout
V K Prest, J A Donaldson, Howard D. Mooers

Bibliographic record

VenueGéographie physique et Quaternaire · 2002
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsGeological Survey of Canada
Fundersnot available
KeywordsGeologyBayGlacial periodPaleontologyGroup (periodic table)BedrockProterozoicArchaeologyOceanographyGeographyTectonics

Abstract

fetched live from OpenAlex

The direction of Wisconsinan glacial dispersion of distinctive Proterozoic erratics derived from the Belcher Group in southeastern Hudson Bay is shown to have been northwestward, westward and southward for hundreds of kilometres across Hudson Bay, Northern Ontario, western Canada, and several adjoining northern States. The most distinctive of these erratics, termed "omars", are composed of massive siliceous wacke characterized by buff-weathering calcareous concretions; these erratics were derived from the Omarolluk Formation of the Belcher Group, exposed in the Belcher Islands of eastern Hudson Bay, and probably underlying much of the southern part of this inland sea. Far less common but equally distinctive are erratics of red oolitic jasper that were derived from the Kipalu Formation of the Belcher Group. In parallel with the now widely accepted field term "omar", we introduce the term "kipalu" for such erratics of oolitic jasper. A map showing the distribution of the distinctive erratics, in relation to indicators of Wisconsinan glacier movement, provides the basis for inferring at least two discrete glaciations that produced several major ice lobes. This paper summarizes the field observations of numerous Canadian and American earth scientists, traces the evolution of thought on provenance of the distinctive erratics, and outlines the criteria for distinguishing "true" omars from erratics derived from other bedrock sources of concretion-bearing wackes.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.586
Threshold uncertainty score0.999

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 studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.015
GPT teacher head0.223
Teacher spread0.208 · 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.

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

Citations39
Published2002
Admission routes3
Has abstractyes

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