Entretien avec Lahou Keita, spécialisée en ingénierie de la maintenance aéronautique et entrepreneure fondatrice avec sa sœur Fatou Keita de Keitas Systems au Canada
Bibliographic record
Abstract
Lahou Keita est Inspectrice avion (inspections achats / ventes d’avions), spécialisée en ingénierie de la maintenance aéronautique. Elle a débuté sa carrière aéronautique aux Aéroports de Paris, à Roissy Charles de Gaulle, au département de centrage des avions. Lahou Keita a continué son cursus au support Clients pour la gestion de maintenance chez Dassault Falcon Service (filiale de Dassault Aviation) à l’aéroport du Bourget. Elle a poursuivi sa carrière en Suisse (à Genève) dans des centres de maintenance tels que Ruag Aviation et Jet Aviation. Diplômée en langues étrangères appliquées, Lahou Keita est polyglotte, et parle notamment le finnois. La société Keitas Systems France a été constituée à Nantes en 2011. L’entreprise Keitas Systems Canada a été créée quant à elle à Québec en 2019. Depuis 2011, Keitas Systems a pour objectifs d’améliorer le quotidien des centres de maintenance aéronautique et des opérateurs d’avions du monde entier : réductions des coûts, optimisation de la chaîne de valeur…
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.071 | 0.010 |
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".