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Record W6962745377 · doi:10.17632/t7wvtrk28y

Preliminary retrievals of deformation rates based on 2017-2023 Sentinel-1 data computed with the MSBAS system.

2023· dataset· en· W6962745377 on OpenAlexaboutno aff

Bibliographic record

VenueMendeley Data · 2023
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsDeformation (meteorology)Speckle patternGlacierChinaData processing

Abstract

fetched live from OpenAlex

Supplementary information for the manuscript Deformation rates for North America and Eurasia from Sentinel-1 DInSAR: processing methodology with examples Preliminary retrievals of deformation rates during 2017-2023 computed from Sentinel-1 data with the MSBAS system Part I: Canada (Ascending) Part II: Canada (Descending) Part III: China (Ascending) Part IV: China (Descending) Part V: Russia (Ascending) Part VI: Russia (Descending) Part VII: Central Asia and the Caucasus Part VIII: Glaciers (from speckle offsets), Canada Part IX: Glaciers (from speckle offsets), Russia For additional information contact Sergey Samsonov at sergey.samsonov@nrcan-rncan.gc.ca.

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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.295
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0140.007
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.019

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 head0.106
GPT teacher head0.329
Teacher spread0.223 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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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