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Record W3186280491 · doi:10.5539/ijef.v13n9p1

IFRS 16 - Impact on the Assets of the Major Airlines Operating in Brazil

2021· article· en· W3186280491 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.

venuePublished in a venue whose home country is Canada.
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

VenueInternational Journal of Economics and Finance · 2021
Typearticle
Languageen
FieldDecision Sciences
TopicBusiness and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsProfitability indexBusinessPosition (finance)AccountingEarnings before interest and taxesCapital structurePaymentValue (mathematics)Return on capital employedFixed assetFinanceEconomicsFinancial capitalProduction (economics)Capital formationDebt

Abstract

fetched live from OpenAlex

The article aims to study the impacts that the adoption of IFRS 16 will have on the financial position, that is, what will be the impact on the total value of assets of airlines operating in the Brazilian market. It is evident that the new accounting of aircraft acquired through operating leases, an essential tool for any company in the sector, is fully in line with the essence of the operation. Therefore, the authors structured the methodology through a comparison of indicators between 3 companies in the Brazilian airline industry, together with data collection through accounting information obtained in explanatory notes on future payments of operating leases. The findings show that, with IFRS 16, there were significant changes in the indebtedness indicators of companies, due to the significant changes in the accounting of assets, affecting the capital structure and profitability of companies.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.568
Threshold uncertainty score0.112

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0000.000

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 head0.057
GPT teacher head0.355
Teacher spread0.299 · 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