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Record W7133380544

Comparison of established methodologies for reserve report of oil companies on the stock exchanges of canada, united states and Colombia. 3

2014· article· es· W7133380544 on OpenAlexaboutno aff
Diana Carolina Rangel Barrera

Bibliographic record

VenueUniversidad Industrial de Santander · 2014
Typearticle
Languagees
FieldBusiness, Management and Accounting
TopicFinancial Reporting and Valuation Research
Canadian institutionsnot available
Fundersnot available
KeywordsStock exchangeForeign exchange
DOInot available

Abstract

fetched live from OpenAlex

El valor de una compañía petrolera es en esencia distinto al de los demás tipos de compañías, teniendo en cuenta que su principal activo que son las Reservas no hace parte del balance general, ni del estado de pérdidas y ganancias. Por esta razón, algunas de las principales Bolsas de Valores del Mundo desarrollaron metodologías específicas para el reporte de Reservas de las compañías petroleras que están listadas en sus mercados. Considerando el auge de los títulos de las compañías petroleras en la Bolsa de Valores de Colombia, este trabajo busca comparar las metodologías que para el reporte de Reservas han sido implementadas por las Bolsas de Valores de Estados Unidos, Canadá y Colombia. El documento presenta los conceptos básicos del Valor de una Compañía Petrolera, las definiciones de Reservas emitidas y/o adoptadas por diferentes entidades como SEC, COGEH, ANH. Muestra la comparación entre las metodologías establecidas para el reporte de reservas en las Bolsas de Valores objeto de este trabajo y se identifican diferencias sustanciales y el impacto que tienen en la estimación del valor de dichas compañías, a través de su principal activo: Las reservas. Se desarrolla el rol de los Evaluadores/Auditores de Reservas y se realiza una clasificación de las compañías que operan en Colombia según su tamaño y bolsa en la que están listadas. La monografía permite concluir que la Bolsa de Valores de Colombia no ha implementado ninguna metodología para el reporte de Reservas y presenta los potenciales riesgos de esta falencia. 1 Trabajo

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)0.007
metaresearch head score (Gemma)0.030
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.421
Threshold uncertainty score0.847

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.030
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0170.014
Science and technology studies0.0010.000
Scholarly communication0.0040.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0150.002

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 head0.212
GPT teacher head0.372
Teacher spread0.160 · 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
Published2014
Admission routes1
Has abstractyes

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