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Record W4393242252 · doi:10.54097/hbem.v21i.14415

Analysis on Unusual Current Ratio of Apple Based on Annual Report 2017-2023

2023· article· en· W4393242252 on OpenAlexaff
Julian Zhu

Bibliographic record

VenueHighlights in Business Economics and Management · 2023
Typearticle
Languageen
FieldDecision Sciences
TopicImpact of AI and Big Data on Business and Society
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCurrent (fluid)Environmental scienceGeologyOceanography

Abstract

fetched live from OpenAlex

Apple, as the leading company of technology industry, plays a significant role on the manufacture and sale of electronical devices. Therefore, it is worth to analyze its financial situations. However, its most updated data of unusual current ratio has not been widely noticed. On one hand, its current ratio has dropped to less than 1 since March 2022, underlying its current asset is not adequate to cover up its current debt. On the other hand, its high profitability ratio shows Apple appears to be a fairly prosper firm and is nearly impossible to fall in the foreseeable future. This paper focuses on Apple’s balance sheet and income sheet by using the method of collecting the data from Apple’s financial report from 2017 to 2023 and then analyzing the correlation. The result of the research demonstrates that Apple is still considered safe despite its low liquidity and high risk since it has enormous cash and market securities to pay off its debt.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.521
Threshold uncertainty score0.611

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
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 head0.074
GPT teacher head0.343
Teacher spread0.269 · 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.

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
Published2023
Admission routes1
Has abstractyes

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