MétaCan
Menu
Back to cohort
Record W774757240

SELLING TRAVEL WHERE CASH IS STILL KING

2005· article· en· W774757240 on OpenAlexaboutno aff
Michele Mcdonald

Bibliographic record

VenueAir transport world · 2005
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicAviation Industry Analysis and Trends
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessThe InternetCashPaymentAir travelChinaAviationFinanceCredit cardCommerceMarketingAdvertisingEngineering
DOInot available

Abstract

fetched live from OpenAlex

This article addresses the use of credit cards as payment for air travel. As Internet technologies become increasingly popular and available to consumers, nearly all air carriers offer “ticketless” travel paid for via the Internet. Although travel paid for by credit is mostly only prevalent in cultures where borrowing is acceptable (notably the United States, United Kingdom, Australia, Canada, Hong Kong, and Singapore), the rest of the world, including industrialized nations, generally prefer to pay with cash. However, as China is predicted to become the second largest aviation market by 2020, its reticence to accept the credit-driven Internet payment system worries industry analysts. Despite this hurdle, companies are rigorously searching for technologies to accommodate customers, including technologies such as BilltoBill, debit cards, ELV, Bibit Global Payment Services, and many others.

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 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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.756
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.223
Teacher spread0.189 · 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 teacher head, not a consensus.

Study designObservational
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
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueAir transport worldSame topicAviation Industry Analysis and TrendsFrench-language works237,207