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Record W3029952823 · doi:10.4324/9781003022077-7

Beach Processes in an Arctic Environment

2020· book-chapter· en· W3029952823 on OpenAlexaboutno aff
S. B. McCann

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicOil Spill Detection and Mitigation
Canadian institutionsnot available
Fundersnot available
KeywordsArcticThe arcticOceanographyEnvironmental scienceGeology

Abstract

fetched live from OpenAlex

Data on ice conditions, ablation sequences, beach profiles, beach sediments, wave conditions, and freeze-up sequences have been collected during four field seasons, 1968-71, in the Radstock Bay area of S.W. Devon Island (74°N, 91°W) in the Canadian Arctic Archipelago. From these observations it is possible to build up a reasonable picture of the beach conditions and annual regime in this particular area of the Arctic and, perhaps more important, to gain an insight into the year to year variation in the intensity of operation of beach processes. In this latter regard the field data have been supplemented by wind data from the Resolute meteorological station and ice reconnaissance data for the Barrow Strait-Lancaster Sound sea area, for a ten year period 1959-1968. The paper considers the special characteristics of Arctic beaches and discusses the annual beach regime in the study area. Considerable importance is attached to freeze up conditions in the fall as one determinant of beach conditions and the operation of beach processes during the following summer. The magnitude and frequency of periods of significant wave action are considered in relation to the probability of simultaneous occurrence of ice free ocean, suitable winds and ice free beaches, and the effects of three major storms during the study period are evaluated. The study has applications in the selection of landing beaches and in the construction of coastal installations.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.959
Threshold uncertainty score0.997

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0220.004

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 head0.015
GPT teacher head0.201
Teacher spread0.186 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations5
Published2020
Admission routes1
Has abstractyes

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