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Record W2890006994 · doi:10.5430/bmr.v7n3p1

Operation of the Information Monitoring System for the Optimization of the Processing Time and the Dissemination of Financial Data

2018· article· en· W2890006994 on OpenAlexvenueno aff
Hanen Khanchel, Mohamed Afif Lakhoua, Karim Ben Kahla

Bibliographic record

VenueBusiness and Management Research · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBig Data and Business Intelligence
Canadian institutionsnot available
Fundersnot available
KeywordsAnticipation (artificial intelligence)Process (computing)Information processingComputer scienceDisseminationFinanceInformation systemGridInformation overloadData scienceBusinessArtificial intelligencePsychologyWorld Wide WebTelecommunications

Abstract

fetched live from OpenAlex

In this paper, we propose the concept of "information monitoring system "; we indicate its usefulness in the process of informative anticipatory system, in the face of the problem of financial information overload caused by the use of ICT. We present a grid of analysis of the accounting process in an indebted company. The concept is useful when the information intelligence is oriented "exploitation of the information anticipatory" for the anticipation, these being embedded in large financial data. Our experimentation on the problem studied will show us that these tools are effective to optimize the time of processing and dissemination of financial information for decision-making.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.809
Threshold uncertainty score0.476

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.080
GPT teacher head0.345
Teacher spread0.265 · 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 designSimulation or modeling
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
Published2018
Admission routes1
Has abstractyes

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