Proposal for an administrative procedures manual with a biosafety approach after Covid-19
Bibliographic record
Abstract
The present research seeks to create an organizational structure design for the Restaurant "Mi Galito", to implement sales and distribution strategies in order to contribute in the foundation of solid bases to be able to compete in the current market; due to the current conditions in which the business is found as a result of the pandemic by "Covid-19". Therefore, a descriptive, qualitative-quantitative research was developed with the use of methods in the theoretical order and techniques in the practical order such as interviews and surveys to the main actors involved. As a result, it was found that the business has a high acceptance rate of 90% for the taste of its dishes and with a 100% satisfaction regarding the service, for which the variety of flavors and its low prices are the qualities valued by external customers; also, it was known that the restaurant was not operational during the second quarter of 2020 due to the pandemic that represented a reduction in demand even in the process of reopening. Organizational change due to contingencies in the context makes it imperative to analyze the organizational structure of a business in order to adapt to current demands, obtain profits or survive in the market.
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 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 | 0.083 | 0.129 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.186 | 0.130 |
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".