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Record W2994786645 · doi:10.1139/geomat-2019-0021

The U.S. is replacing NAD83 with NATRF2022: what this means for Canada

2019· article· en· W2994786645 on OpenAlexafffundvenueabout
Caroline Erickson, Geoff Banham, Ron Berg, Joey Chessie, M. Craymer, Brian Donahue, Renée Tardif, Yves Thériault, M. Véronneau

Bibliographic record

VenueGEOMATICA · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysics and Gravity Measurements
Canadian institutionsMinistère des Ressources naturelles et des Forêts (Québec)Government of New BrunswickUniversity of New BrunswickNatural Resources CanadaAlberta Environment and Protected AreasMinistry of Transportation of OntarioGeological Survey of Canada
FundersNatural Resources Canada
KeywordsNorth American Datum of 1927Geodetic datumReference frameGeographyWork (physics)Frame (networking)Modernization theoryGeospatial analysisRegional sciencePolitical scienceGeodesyCartographyComputer scienceEngineeringTelecommunicationsLaw

Abstract

fetched live from OpenAlex

In 2022, the U.S., as part of its reference system modernization, will replace its North American Datum of 1983 (NAD83) with a new North American Terrestrial Reference Frame (NATRF2022), creating 1.3 to 1.5 m horizontal coordinate differences at the Canada–U.S. border with respect to Canada’s NAD83(CSRS). Never before have such significant differences existed between our two countries’ reference frames. This paper reviews why the U.S. is making this change and then looks at Canada’s situation with respect to reference frames. There are compelling reasons for Canada to follow suit and move to NATRF2022 within a decade, but there are also major challenges. Whether or not Canada follows the same path, there is much work to be done to prepare Canada for the U.S.’ move to NATRF2022. This paper is intended as a first step to inform the Canadian geospatial community of the U.S.’ move to NATRF2022 and what it means for Canada.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.038
Threshold uncertainty score0.242

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0050.002
Scholarly communication0.0060.003
Open science0.0030.002
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0380.009

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 head0.008
GPT teacher head0.176
Teacher spread0.168 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations1
Published2019
Admission routes4
Has abstractno

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