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Record W7139540346

Bonneville Basin Satellite Image

2023· article· W7139540346 on OpenAlexaboutno aff
Ellie Leydsman McGinty, R. Douglas Ramsey

Bibliographic record

VenueDigital Commons - USU (Utah State University) · 2023
Typearticle
Language
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsStructural basinShoreTerrainBasin and Range ProvinceMultispectral imageSnowSatellite imagerySatellite
DOInot available

Abstract

fetched live from OpenAlex

As a contribution to the Utah as Art collection created by UtahView, a member of the AmericaView consortium (https://americaview.org/), this image of the Bonneville Basin, Utah is intended to act as an educational resource to increase interest in the contributions of remote sensing satellites as an aid to Earth resource management. The Bonneville Basin is a system of endorheic basins located in northwestern Utah, once occupied by ancient Lake Bonneville, a Pleistocene pluvial lake that occupied the area from 32,000 to 14,500 years ago. Remnants of Lake Bonneville include the Great Salt Lake, Sevier Lake, and Utah Lake. Prominent features include the Newfoundland Range (center right) and the Pilot Range along the western edge. Light to deep blue areas represent variations in standing water and soil moisture, with lighter blues composed of snow along the mountain ranges, and deeper blues representing frozen or standing water. This image of the Bonneville Basin was captured on December 17, 2019, by the Multispectral Imager onboard the European Space Agency Sentinel-2A satellite. The image was overlain onto terrain relief data and enhanced to emphasize water and soil moisture characteristics.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.129
Threshold uncertainty score0.290

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0870.026

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 head0.017
GPT teacher head0.200
Teacher spread0.182 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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