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Record W2793629851

Atlas of the Land Entry Ports on the Canada-US Border

2010· article· en· W2793629851 on OpenAlexaboutno aff
D. L. Davidson, Bryant Hammond, Kathlleen Mintz

Bibliographic record

VenueWestern CEDAR (Western Washington University) · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsAtlas (anatomy)GeographyGeology
DOInot available

Abstract

fetched live from OpenAlex

This atlas identifies the names and locations of all legal land crossing points along the Canada – U.S. border. We omit portsof-entry that are considered “land” ports by the Canada Border Services Agency (CBSA) and/or U.S. Customs and Border Protection (USCBP) but that are actually served by boat (e.g., the ferry landing at Anacortes, WA). Each depicted point is one at which a vehicle can directly travel by road (or railroad) from U.S. to Canadian soil. There are 146 in all, of which 26 are rail lines and 120 are roadways (19 bridges, 1 tunnel, and 100 roads). Two of the 120 roadways (Stewart, BC, and Four Falls, NB) lack a USCBP facility, while all others are staffed by both agencies. For record-keeping purposes, USCBP groups its 118 roadway facilities into 80 “master” ports, with data from neighboring small ports aggregated under the name of the master port.

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)0.000
metaresearch head score (Gemma)0.002
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: Other · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.175

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0110.028
Science and technology studies0.0040.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0190.002

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 head0.009
GPT teacher head0.223
Teacher spread0.214 · 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
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

Citations4
Published2010
Admission routes1
Has abstractyes

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