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Record W2078314664 · doi:10.1111/1911-3838.12041

Bonbons Hansel et Gretel inc.

2015· article· en· W2078314664 on OpenAlexaffvenue
Louise Martel, Diane Paul

Bibliographic record

VenueAccounting Perspectives · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Reporting and Valuation Research
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsGoodwillHumanitiesArtBusinessFinance

Abstract

fetched live from OpenAlex

Bonbons Hansel and Gretel inc. (BHGI) has acquired all shares of Les délices de Fée Dragée (LDFD). That French private company has made its mark in 50 years with a secret recipe of natural licorice candy that consumers absolutely love. BHGI now possesses an advantage over its domestic competitors with this recipe and the client list of LDFD, but the French factory will need to be refurbished in ten years. During due diligence, BHGI learns that a lawsuit was filed against LDFD. It is time to account for the acquisition and to determine the amount of goodwill. Headaches are anticipated when assessing the fair value of assets acquired, especially when considering the various possible assessment methods and assumptions to be used as input data for valuations approaches.

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)0.005
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 score0.344
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.093
GPT teacher head0.342
Teacher spread0.249 · 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

Citations2
Published2015
Admission routes2
Has abstractyes

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