Quri: galletas de avena enriquecidas con cushuro
Bibliographic record
Abstract
The many occupations that people perform daily do not allow them to dedicate themselves to the activities that are fundamental to lead a healthy lifestyle. One of these activities is food, the same one that has been neglected, which, added to the proliferation of fast foods, generates a nutritional deficit in society. \nThis business is the development and marketing of a nutritious snack enriched with cushuro, in the form of cookies, which seeks to help reduce the effects of the reality that is currently being experienced. The main source of income will be the sale of these cookies to people who consider it necessary to improve their nutrition. \nFor the start-up of the project an initial investment of S / 89,847.00 is needed, which will be paid by 60% by the creators of the project and an investor who is willing to contribute the remaining 40% is looked for. \nAccording to projected cash flows, within the last quarter of the first year of operations, the project starts generating profits, so the recovery of the total amount invested is guaranteed, plus the respective profit, at the end of the 3 years the project lasts. \nIt is considered that the business is viable because there is a growing tendency on the part of people to care for their food, so the consumption of products considered natural and nutritious is increasing significantly in the market.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.124 | 0.022 |
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".