Fractality in Manufacturing Industry
Bibliographic record
Abstract
Fractal theory, a topic first introduced by Mandelbrot in 1970, has nevertheless witnessed a great boom in the field of science in this last decade. In this article, we analyze time series (TS), behavior of the variable, cost of that sold (CS), and we assume and demonstrate that there is fractality in the system for manufacturing companies in Mexico. We analyzed 30 companies that are listed on the Mexican stock exchange, obtaining 23 data for each organization, taking a period stretching from the first quarter of 2010 to the third quarter of 2015, and obtaining a total of 704 data. We only selected 512 for each one of the 30 TS, using fractal interpolation (FI) as the method for generating data in TS. TS 30 was characterized from the point of view of Visual Recurrence Analysis (VRA) software. It is apparent that in 80% of the companies analyzed, the dynamics of the CS system were elucidated using 4 variables.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".