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Record W2972980450 · doi:10.1080/20964471.2019.1658494

On the isolatitude property of the rHEALPix Discrete Global Grid System

2019· article· en· W2972980450 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.

Bibliographic record

VenueBig Earth Data · 2019
Typearticle
Languageen
FieldComputer Science
TopicDistributed and Parallel Computing Systems
Canadian institutionsUniversity of CalgaryUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGeodetic datumProperty (philosophy)Geospatial analysisComputer scienceGridRing (chemistry)IdentifierConstant (computer programming)Topology (electrical circuits)GeodesyGeologyRemote sensingMathematics

Abstract

fetched live from OpenAlex

Digital Earth frameworks provide a way to integrate, analyze, and visualize large volumes of geospatial data, and the foundation of such frameworks is the Discrete Global Grid System (DGGS). One approach in particular, the rHEALPix DGGS, has the rare property of distribution of cell nuclei along rings of constant latitude (or isolatitude rings). However, this property is yet to be explored. In this paper, we extend existing work on the rHEALPix DGGS by proposing a method to determine the isolatitude ring on which the nucleus of a given cell falls by converting a cell identifier to isolatitude ring without recourse to geodetic coordinates. In addition, we present an efficient method to calculate the geodetic latitude of a cell’s nucleus via its associated isolatitude ring. Lastly, we use the proposed methods to demonstrate how the isolatitude property of the rHEALPix DGGS can be utilized to facilitate latitudinal data analysis at multiple resolutions.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.754
Threshold uncertainty score0.817

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0040.001
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 head0.040
GPT teacher head0.242
Teacher spread0.201 · 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