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Record W2194376356 · doi:10.1002/ppp.1867

Reconstructing Periglacial Geomorphology: The Contribution of J. Ross Mackay

2015· article· en· W2194376356 on OpenAlexaff
Michael Church

Bibliographic record

VenuePermafrost and Periglacial Processes · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsLandformGeologyPermafrostGeomorphologyField (mathematics)Physical geographyGeography

Abstract

fetched live from OpenAlex

Abstract Ross Mackay's contributions to periglacial geomorphology are commonly regarded as the fruit of solo inspiration. In fact, his work is an exemplary product of its time. At the outset of his career, geomorphology was entering a radical transformation from interpretive study of landscape history towards quantitative study of landscape‐forming processes. Early periglacial geomorphology was concerned mainly with attempting to infer historical environmental conditions on the periphery of the great Pleistocene ice sheets and Mackay's earliest works are historically oriented accounts of regional geography. From 1960, however, his work, following the new perspective, was based on quantitative measurement of landforms and land‐forming processes, both in the field and on maps, and application of physical theory to interpret his observations. He focused attention on individual periglacial landforms that had hitherto been only superficially described. Outstanding aspects of Mackay's contributions are his genius for making critical field observations and his ability to use them to test geophysical theory. He was one of a very small number of pioneers who reconstructed periglacial geomorphology. Copyright © 2015 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.025
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.258
Teacher spread0.229 · 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

Citations11
Published2015
Admission routes1
Has abstractyes

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