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Record W659534410

IT GOT WORSE : US MAJOR AIRLINES FOLLOW UP A YEAR OF RECORD LOSSES... WITH ANOTHER YEAR OF RECORD LOSSES

2003· article· en· W659534410 on OpenAlexaboutno aff
Paul L. Flint

Bibliographic record

VenueAir transport world · 2003
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicAviation Industry Analysis and Trends
Canadian institutionsnot available
Fundersnot available
KeywordsRevenueQuarter (Canadian coin)BailoutGovernment (linguistics)BusinessFinanceEconomicsAgricultural economicsGeographyArchaeology
DOInot available

Abstract

fetched live from OpenAlex

A year of record losses for the U.S. majors has been followed by another year of record losses. The 10 largest U.S. airlines collectively lost more money in 2002 than in 2001. That figure includes the $5 billion government bailout distributed in 2001. Again, Southwest did the well, emerging as the only profitable carrier in the group for both periods. The biggest loser was American Airlines parent, AMR Corp. Holiday traffic was stronger than anticipated, creating a fourth-quarter bump, but other unusual charges took away from the bottom line. Fourth-quarter operating revenues rose 14.2%, reducing the combined operating loss to $3.4 billion from $4.8 billion. Revenues for the year declined 7.3%, while operating costs dropped 6.7%. Operating losses for AMR were $3.33 billion, versus $2.47 billion. UAL ended about $300 million than AMR. Figures for other majors are included, along with charts of yields and costs.

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)0.001
metaresearch head score (Gemma)0.006
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: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0030.001
Scholarly communication0.0050.004
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0190.006

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 head0.029
GPT teacher head0.219
Teacher spread0.191 · 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
Published2003
Admission routes1
Has abstractyes

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