MétaCan
Menu
Back to cohort
Record W6993126547

North Dakota Border Planning: Facilitating Transportation Across the Northern Border

2018· other· en· W6993126547 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueRosa P: A digital library for transportation research (United States Department of Transportation) · 2018
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionGestational periodTSG101DiafiltrationLiquationHyporeflexiaDysgeusiaHemopericardiumFusible alloy
DOInot available

Abstract

fetched live from OpenAlex

Border transportation planning involves the development of goals, objectives, and strategies for moving people and goods across the U.S.–Canada border. FHWA leads multiple binational stakeholders to collaboratively create safe and effective crossborder transportation. FHWA also facilitates the development and maintenance of the surface transportation system along the U.S.–Canada border to address existing and anticipated demand for cross border travel and trade while working with federal, state, regional, and local agencies, the private sector, and various stakeholders. In 2016, over 378,000 trucks, 661,000 personal vehicles, and 1.2 million vehicle passengers crossed through the 18 Land Ports of Entry (LPOEs) along North Dakota's 310 miles of shared border with Canada's provinces of Saskatchewan and Manitoba, Canada.1,2\n

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.157
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.005
Science and technology studies0.0010.002
Scholarly communication0.0010.003
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.037
GPT teacher head0.344
Teacher spread0.307 · 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