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Record W7159738340

Efecto de la publicación de resultados financieros sobre la tendencia en bolsa de las acciones del grupo nutresa. 2015-2019

2019· other· es· W7159738340 on OpenAlexaboutno aff
Diana Rosa Arrieta Ballesta, Yuris Ortega Soraca

Bibliographic record

VenueRepositorio Universidad de Córdoba · 2019
Typeother
Languagees
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsEarnings before interest, taxes, depreciation, and amortizationProfitability indexBalance sheetQuarter (Canadian coin)Share priceInvestment (military)Margin (machine learning)Financial analysisFinancial market
DOInot available

Abstract

fetched live from OpenAlex

This monograph focuses on the quarter to quarter analysis and monitoring of the financial statements of the Nutresa Group, specifically the balance sheet and the income statement, through which some profitability indicators such as ROE and ROA are applied. In the same way, Ebitda and its margin are established on the company’s operating in come. However, on the other hand, a fundamental type analysis is carried out on the stock market Price of the shares of Grupo Nutresa and how it has been during the 2015-2019 period, in the same way it is evidenced as the changes presented in their financial statements are reflected in the Price of the shares themselves. That is, investors take into account the results reflected in the financial statements, for the purchase of shares, it can be said that in some way the are assured that their investment is generating the expected profit. Then it can be affirmed that the financial statements do intervene in any way in the Price of the shares of Grupo Nutresa.

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)0.005
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.004
GPT teacher head0.258
Teacher spread0.253 · 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 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
Published2019
Admission routes1
Has abstractyes

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