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Record W591502936

Burkhardt's Bangor Baby

2007· article· en· W591502936 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

VenueTrains · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicTransport and Economic Policies
Canadian institutionsnot available
Fundersnot available
KeywordsBankruptcyRevenueSalaryMillFinanceLivelihoodTrack (disk drive)Economic historyManagementBusinessPolitical scienceEconomicsHistoryEngineeringLawArchaeologyMechanical engineering
DOInot available

Abstract

fetched live from OpenAlex

This article, third in a series on Ed Burkhardt’s rail world, this article focuses on the Montreal, Maine & Atlantic (MM&A) railroad. Prior to Burkhardt’s involvement, the railroad was run as the Bangor & Aroostook, with its origins dating back to 1891. Financial struggles resulted in its bankruptcy in 2002, and in early 2003, the railroad was acquired by Burkhardt’s Rail World and renamed the MMA. The article describes the struggles that the MM&A has faced in the four years since Burkhardt’s purchase. Key to MM&A’s livelihood was the Great Northern paper mill, which provided 25 percent of the railroad’s revenue. However, financial problems forced the mill’s shutdown, which then threw MM&A into salary reductions and layoffs. While new ownership has helped turn the tide for the mill, it is still not smooth sailing for the MM&A. The article describes how the railroad has purchased new maintenance of way equipment, upgraded track, and is prepared for adversity if necessary.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.676
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.022
GPT teacher head0.218
Teacher spread0.196 · 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