Innovative Approaches to Model Visualization for Integrated Management Systems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
With a growing number of standards and their related requirements for manufacturers and/or service providers, there is a need to simplify their application process. The aim of this article is to propose a simplified implementation of multiple management system standards (MSSs) through visualization management. Results of visualization provide a perspective of interrelatedness of requirements of MSSs, and how they fit in the overall context. The three standards used in this project, defined as a complex triplet of integrated management systems (IMSs), are: Quality (QMS), Environment (EMS) and Event Sustainability (ESMS) Management Standards. Visualization is developed by creating clusters using a program intended for creating small world networks. This step is preceded by the creation of a database in a spreadsheet format for data mining, where the requirements are divided into specific and common ones. The main emphasis will be on facilitating the assessment of synergies. The resulting visualized composed cluster model of selected areas includes the clauses. It is possible to further extend the model by adding other standards, depending on needs of interested parties. In essence, the model is a part of visual process, and it simplifies, speeds up and clarifies managerial decision-making processes related to the implementation of the MSSs.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it