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Record W2568187354 · doi:10.5430/ijba.v8n1p50

Study of Behavior of Human Capital from a Fractal Perspective

2016· article· en· W2568187354 on OpenAlexvenueno aff
Leydi Z. Guzman-Aguilar, Angel Machorro-Rodriguez, Tomás Morales Acoltzi, Miguel Montano-Alvarez, Marcos Salazar-Medina, Edna Araceli Romero-Flores

Bibliographic record

VenueInternational Journal of Business Administration · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicComplex Systems and Time Series Analysis
Canadian institutionsnot available
FundersTecnológico Nacional de MéxicoDepartment of Environment and Primary Industries
KeywordsFractalPerspective (graphical)Interpolation (computer graphics)Scheme (mathematics)Computer scienceSeries (stratigraphy)Nonlinear systemCapital (architecture)Scale (ratio)Applied mathematicsEconometricsMathematicsMathematical analysisArtificial intelligenceCartographyGeologyImage (mathematics)GeographyPhysics

Abstract

fetched live from OpenAlex

In the last decade, the application of fractal geometry has surged in all disciplines. In the area of human capital management, obtaining a relatively long time series (TS) is difficult, and likewise nonlinear methods require at least 512 observations. In this research, we therefore suggest the application of a fractal interpolation scheme to generate ad hoc TS. When we inhibit the vertical scale factor, the proposed interpolation scheme has the effect of simulating the original TS.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.180
Threshold uncertainty score0.703

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.040
GPT teacher head0.285
Teacher spread0.245 · 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 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
Published2016
Admission routes1
Has abstractyes

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