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Record W7065473993

Emerging from the Pandemic: Understanding the Canada-US land border requirements

2021· article· en· W7065473993 on OpenAlexaboutno aff

Bibliographic record

VenueWestern CEDAR (Western Washington University) · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicElectrical and Electromagnetic Research
Canadian institutionsnot available
Fundersnot available
KeywordsCLARITYConfusionBorder crossingLand useEasementAir travel
DOInot available

Abstract

fetched live from OpenAlex

The restrictions on ‘non-essential’ travel at land and ferry crossings enacted by Canada and the United States in March 2020 remained largely unchanged for over a year. During the first fifteen months of the restrictions, Canada implemented some exemptions for family members and compassionate reasons and changed some entry requirements, while the US restrictions remained intact. After an unprecedented period of a heavily restricted land border, Canada began to ease restrictions for fully vaccinated US travelers in August 2021, with the US following in November. However, much like the restrictions themselves, definitions and requirements vary by country (and for the US, by mode). Because so many travelers crossing the border are doing so in both directions, the discrepancy between Canadian and US requirements will cause confusion and delays at the border, unless travelers are well educated about what is required by both countries. Canadian entry requirements have already resulted in confusion for travelers, and this situation is likely to worsen when US land border restrictions ease and cross-border travel volumes increase. This Border Brief is intended to provide clarity and guidance on the land border requirements for travelers crossing the Canada–US border, in both directions.

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)0.010
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 score0.081
Threshold uncertainty score0.587

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.003
Science and technology studies0.0120.010
Scholarly communication0.0110.008
Open science0.0020.005
Research integrity0.0030.008
Insufficient payload (model declined to judge)0.0050.001

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 head0.033
GPT teacher head0.264
Teacher spread0.231 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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