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Record W2008480759 · doi:10.1002/ppp.672

Using the MODIS land surface temperature product for mapping permafrost: an application to northern Québec and Labrador, Canada

2009· article· en· W2008480759 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePermafrost and Periglacial Processes · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsUniversity of WaterlooUniversité LavalCenter for Northern Studies
FundersNatural Sciences and Engineering Research Council of CanadaMinistry of Public Security of the People's Republic of ChinaArcticNetJapan Aerospace Exploration AgencyNational Aeronautics and Space Administration
KeywordsPermafrostLand coverModerate-resolution imaging spectroradiometerSnowRemote sensingVegetation (pathology)SpectroradiometerGeologySnow coverSpatial distributionClimatologyPhysical geographyLand useGeomorphologySatelliteGeographyReflectivityOceanography

Abstract

fetched live from OpenAlex

Abstract The Land Surface Temperature (LST) products of the Moderate Resolution Imaging Spectroradiometers (MODIS) aboard NASA's Terra and Aqua satellites were used to develop maps of annual near‐surface temperatures for comparison with the spatial distribution of permafrost and boundaries of the permafrost zones. The methodological approach involved fitting a sinusoidal model over the daily LST readings to reproduce seasonal thermal variations near the ground for each 1‐km 2 pixel. Calculations of mean annual surface temperatures and of thawing and freezing indices led to the development of regional maps, in this case for northern Québec and Labrador. The maps show the expected geographic distribution of near‐surface temperatures and acceptably represent known permafrost boundaries. Ongoing efforts to incorporate snow and vegetation cover from complementary remotely sensed data should improve the ground surface temperature mapping capability based on this approach. Copyright © 2009 John Wiley & Sons, Ltd.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.305
Threshold uncertainty score0.731

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.026
GPT teacher head0.249
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