Bibliographic record
Abstract
Le guide Ulysse Toronto vous revelera tous les secrets de la metropole de l’Ontario et du Canada, cette ville moderne au rythme trepidant qui a tant a offrir. Arpentez ses rues sans fin, grimpez au sommet de ses gratte-ciel, decouvrez ses musees et participez a ses innombrables manifestations culturelles. Afin de mieux vous orienter, le guide Ulysse Toronto propose une dizaine de circuits accompagnes de cartes et de plans precis. Restaurants et etablissements d’hebergement dans toutes les categories de prix, bars et discotheques, description detaillee de tous les attraits (cotes selon un systeme d’etoiles), activites culturelles, fetes et festivals, portrait historique... vous aurez en main tous les renseignements necessaires pour bien profiter de cette ville eclectique, que ce soit pour vos deplacements d’affaires ou pour un sejour de decouvertes.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".