Bibliographic record
Abstract
Chronique Universits fet, les rseaux sociaux numriques constituent des outils de partage d'information et vous pourriez les utiliser davantage pour interagir et changer de l'information avec vos parties prenantes.Deuximement, il est souhaitable d'actualiser rgulirement les informations sur le site internet de votre entreprise et sur vos rseaux sociaux numriques.Mettez vos informations jour et supprimez ce qui ne vous parat plus adapt.Vous pouvez publier des annonces de mesures de continuit de votre activit destination de vos clients ainsi que des mesures de scurit orientes vers vos salaris.Troisimement, vous pourriez dvelopper certaines innovations afin de mieux rebondir aprs la crise.Dans cette perspective, vous pourriez profiter de cette pandmie pour dvelopper un avantage concurrentiel en rpondant des demandes du march et/ou en adaptant votre offre de produits/services.Et pour terminer, soyez proche de vos clients.Vos rseaux sociaux numriques sont devenus les seuls contacts humains en ces priodes de distanciation physique.Vos clients sont confins et passent normment de temps sur leurs crans, profitez de cela pour solidifier vos relations.U En collaboration avec Ulrike Mayrhofer (IAE Nice) Les PME face la crise du Covid-19 Ces entreprises doivent tre particulirement cratives et stratgiques dans leurs efforts de communication.
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 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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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; both teacher heads agree on what is shown here.
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".