Method for Comprehensive Evaluation of Enterprise Core Competence and its Application
Bibliographic record
Abstract
Enterprise core competence is the key for its success. It is important for the investors and management to know the enterprise core competence. In this paper, the indexes and evaluation method for enterprise core competence is discussed. The core competence of China Petrochemical Company (SINOPEC) is evaluated with the model. Key words: Enterprise core competence; Evaluation method; Fuzzy application Resume: Le competence distinctive de l’entreprise est l’element important pour sa reussite. C’est important pour les investisseurs et les managers de connaitre les competences distinctives de l’entreprise. Dans cet article, des indices et des methodes d’evaluation sur les competences distinctives de l’entreprise ont ete etudies. Les competences distinctives de la Compagnie petrochimique de la Chine (SINOPEC) ont ete evaluees avec cette methode. Mots-Cles: competence distinctive de l’entreprise; methode d’evaluation; application floue
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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 | 0.012 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".