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Record W3091855545 · doi:10.5430/ijfr.v11n5p353

Artificial Intelligence and Its Use in Financial Markets

2020· article· en· W3091855545 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Financial Research · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicEconomic and Technological Developments in Russia
Canadian institutionsnot available
FundersKazan Federal University
KeywordsProcess (computing)Financial servicesCompetition (biology)Big dataBusinessBusiness processEmerging technologiesInformation technologyProcess managementFinanceMarketingIndustrial organizationComputer scienceWork in processArtificial intelligence

Abstract

fetched live from OpenAlex

The global financial system is currently at a new stage of its development, which is characterized by the introduction of information and communication technologies in all financial spheres. They allow improving business processes and company management and the process of providing services, as they enable organizations to receive more information about their customers and consumers, therefore, to provide better financial services that meet the requirements of customers.In the process of digitalization of the economy, a large role is played by banking organizations. In the conditions of increased competition in the market, banks are forced to continually improve their activities and introduce the most advanced technologies for carrying out business processes and working with clients. One of the most state-of-the-art technologies is artificial intelligence and Big Data. This technology is a combination of technologies targeted at processing vast amounts of data, and the ability to process fast incoming data in large volumes.

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.

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)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.494
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.274
GPT teacher head0.432
Teacher spread0.158 · 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