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Record W2011672813 · doi:10.1002/ppp.612

Interchangeability of mountain permafrost probability models, northwest Canada

2008· article· en· W2011672813 on OpenAlexafffundabout
Antoni G. Lewkowicz, Philip P. Bonnaventure

Bibliographic record

VenuePermafrost and Periglacial Processes · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Foundation for Climate and Atmospheric Sciences
KeywordsPermafrostElevation (ballistics)InterchangeabilityGeologyTransectLogistic regressionPhysical geographyEnvironmental scienceHydrology (agriculture)StatisticsGeotechnical engineeringGeographyMathematicsGeometryComputer science

Abstract

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Abstract Spatial models of mountain permafrost probability based on measurements of the basal temperature of snow (BTS) and ground‐truthing were developed for three study areas located >200 km apart. The interchangeability of these locally derived empirical‐statistical models was examined by predicting BTS values from the equations developed at the other two sites, and using logistic regression to relate these modelled values to the local ground‐truthed data. Equations for two of the areas were effectively interchangeable, producing permafrost extent predictions within 2% of each other, and permafrost probabilities within ±0.1 for more than 85% of the cells. Predictions were much less similar when their equations were applied to the third area and when its equation was applied to them. Model interchangeability appears to depend on where a site lies on a continuum from elevation controlled (infinite ratio of the standardised coefficient of elevation to that of potential incoming solar radiation in the BTS equation), to radiation dominated (ratio much less than unity of the same variables). Extensive ground‐truthing is essential, helping to constrain the logistic regression and hence the overall permafrost percentage. Additional investigations are needed to relate these ratios to regional climate in order to allow the spatial interpolation of permafrost probability models across the North American Cordillera. Copyright © 2008 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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.214
Threshold uncertainty score1.000

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 studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.047
GPT teacher head0.219
Teacher spread0.171 · 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 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

Citations31
Published2008
Admission routes3
Has abstractyes

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