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Record W1507929221

Remote Predictive Mapping 4. Utilizing High Resolution Satellite Imagery, Western Minto Inlier, Victoria Island, NWT

2012· article· en· W1507929221 on OpenAlexaffvenue
Pouran Behnia, R H Rainbird, Jeff Harris

Bibliographic record

VenueGeoscience Canada · 2012
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsGeological Survey of Canada
Fundersnot available
KeywordsGeologyGeologic mapDolostoneLithologyQuadrangleBedrockGeomorphologySedimentary rockRemote sensingCartographyPaleontologyCarbonate rockGeography
DOInot available

Abstract

fetched live from OpenAlex

The very high spatial resolution and stereo capability of GeoEye-1 images were utilized to map the geology of a part of the western Neoproterozoic Minto Inlier on Victoria Island. To optimize the results of predictive mapping, a LANDSAT-7 image together with a SPOT-5 image were also used in concert with the GeoEye-1 images. The predictive bedrock geology map, interpreted based on 3D stereo visualization, presents much more detailed geological information compared to the existing 1:500,000 scale geological map of the area. The high spatial and moderate spectral resolution of GeoEye images allowed us to distinguish a black shale unit (black shale member), and resolve subtle spectral and textural differences between massive stromatolitic dolostone and dolostone containing fine-grained interlayers in an upper carbonate member. As well, an important distinction could be made between Proterozoic sedimentary strata and unconformably overlying interlayered sandstone and carbonate rocks of Cambro-Ordovician age. The SWIR bands in the LANDSAT and SPOT images proved to be very useful in identifying gabbro sills. A geological map, based on field work, was used to evaluate the remote predictive map. Comparison of the predictive map with the field map shows that the two maps look similar in terms of the regional distribution of the lithological units; however, there are discrepancies between the two maps, especially in areas in which the bedrock is covered by glacial sediments and/or other overburden materials. The spectral similarity between different stratigraphic units comprising similar rock types, also contributed to differences between the predictive map and the field map.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.747
Threshold uncertainty score0.934

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.013
GPT teacher head0.208
Teacher spread0.194 · 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 designNot applicable
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
Published2012
Admission routes2
Has abstractyes

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