The creation of a center of technology watch and competitive intelligence. Application to the institute for research and industrial affiliation of ITB (Bandung Institut of Technology)
Bibliographic record
Abstract
Nous allons aborder la problématique indonésienne face au marché globale par la création d'un centre de veille et d'intelligence compétitive " CEVIC ". Ce centre est très important et il sera très utile pour les entreprises, les autres institutions pour la recherche d'information stratégique et critique (IST). En Indonésie, l'apparition du système d'autonomie permet à chaque région de se développer dans de meilleures conditions et d'établir des échanges concurrentiels au niveau national ainsi qu'au niveau international. Par conséquent, l'IST est extrêmement vitale pour chaque région et aussi pour les entreprises existantes. CEVIC va aider chaque région à gérer et à commercialiser leurs richesses et les entreprises tout spécialement dans le domaine de la recherche de l'IST pour supporter leurs activités. CEVIC sera implanté à l'Institut pour la Recherche et l'Affiliation Industrielle " LAPI-ITB ".
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.015 | 0.011 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.028 | 0.005 |
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".