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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".