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Record W6907213781 · doi:10.18739/a2ww7719j

Quantifying river migration rates in the Yukon River Watershed from optical satellite imagery, Alaska, 2016-2022

2024· dataset· en· W6907213781 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueUC Santa Barbara · 2024
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsHydrology (agriculture)ErosionWatershedSatelliteAerial photographyRiver deltaDrainage basinBeaver

Abstract

fetched live from OpenAlex

This dataset describes measurements of river migration rates (averaged over the period 2016-2022) in three locations within the Yukon River Watershed: Huslia, Alaska (AK) (65.700 N, 156.387 W), Beaver, AK (66.362 N, 147.398 W), and Alakanuk, AK (62.685 N, 164.644 W). Huslia is located on the Koyukuk River and Beaver and Alakanuk are located on the Yukon River. The river migration rates are quantified from sub-pixel correlation of optical satellite imagery (Sentinel-2 imagery, 10 meter (m) spatial resolution), following the methodology of Geyman et al. (2024). The methodology allows for the detection of riverbank erosion at scales approximately 5-10 times smaller than the pixel size, so the detection threshold is 1-2 m over the approximately 7-year interval, corresponding to a migration rate of 0.1 to 0.3 m/year. The motion of the eroding and accreting sides of the river are quantified separately. The river migration rate datasets are made available as georeferenced shapefiles.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.148
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.150

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 head0.030
GPT teacher head0.297
Teacher spread0.266 · 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

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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