COBIT, Herramienta de Control en la Gestión Empresarial
Bibliographic record
Abstract
In line with new business needs and trends such as: “COSO (Committee of Sporisoring Organization of the treadway Commission Internal Control-Integrated Framework, 1992 in the US, Cadhuay in the United Kingdom, CoCo in Canada and King in South Africa, and the coexistence of control models at the information technology levels such as: Security Code of conduct of the DTT (Department of Industry and Commerce, United Kingdom) and the Security Handbook of Nist (National Institute of Standards and technology, USA).” Given the need that the aforementioned models do not provide a complete and usable control model in business management, the ISACF (Information Systems Audit an Control foudation) and ITGI (Governance Institute), develop COBIT to cover the pre-existing vacuum to achieve the aims planned in the organizations, with the development with the new point of view that the new information technologies plan. COBIT integrates and consolidates rules and regulations already indicated by the aforementioned institutions.
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 | 0.012 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.015 | 0.007 |
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".