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Record W2034547919 · doi:10.4113/jom.2010.1142

Subglacial landforms in northern Manitoba, Canada, based on remote sensing data

2010· article· en· W2034547919 on OpenAlexafffundabout
Michelle Trommelen, Martin Ross

Bibliographic record

VenueJournal of Maps · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Waterloo
FundersNatural Resources CanadaUniversity of Waterloo
KeywordsDrumlinMoraineGeologyLandformGlacierGlacial landformShuttle Radar Topography MissionIce sheetIce streamGeomorphologyDigital elevation modelPhysical geographyRemote sensingGeographyCryosphereOceanographySea ice

Abstract

fetched live from OpenAlex

Please click here to download the map associated with this article. This paper presents a new subglacial landform map for northern Manitoba (58°-60° N). The region was formerly covered by the Laurentide Ice Sheet and is located at the southern margin of the Late Wisconsinan (∼25-10 Ka BP) deglacial Keewatin Ice Divide just west of Hudson Bay. Mapping was focused on determining the location and orientation of streamlined landforms (drumlins and megaflutes), Rogen moraines, and eskers for the 109,366 km2 region. Based on the theory that landforms such as drumlins and Rogen moraines all result from subglacial ice flow processes, this map forms the basis for reconstruction of ice flow sets that indicate past glacial phases in northern Manitoba. It shows that the geomorphologic record, and hence ice flow history, is more complex than previously reported. There are several successive generations of ice flow indicators superimposed on top of each other, sometimes at abrupt (90°) angles. Special attention is paid to the location and ridge crest orientation of Rogen moraines in northern Manitoba. Hence the map also provides insights into the characteristics of Rogen moraines in northern Manitoba, which are critical for investigating formative processes. 11,007 individual landforms were mapped using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) satellite imagery in combination with a Shuttle Radar Topography Mission (SRTM) digital elevation model and several SPOT 4 satellite images. The results are presented as a printable map at 1:1,125,000 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 score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.028
GPT teacher head0.212
Teacher spread0.184 · 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

Citations13
Published2010
Admission routes3
Has abstractyes

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