Bibliographic record
Abstract
Avec le guide de voyage Ulysse Vancouver, Victoria et Whistler, decouvrez la dynamique et irresistible metropole de la Colombie-Britannique, Vancouver, avec ses quartiers multiethniques et ses magnifiques parcs. De Gastown, Kitsilano, False Creek et Burrard Inlet a Mount Pleasant, Granville Island et Stanley Park, les differents circuits de ce guide Ulysse vous devoilent toutes les splendeurs de la celebre « ville de verre ». Visitez aussi l'Inner Harbour et la Scenic Marine Drive de Victoria, la capitale de la Colombie-Britannique a la couleur britannique legendaire, et voyagez jusqu'a Whistler, paradis du plein air, ou vous pourrez pratiquer une foule d'activites exterieures en toutes saisons. Des excursions dans l'ile de Vancouver et dans les Southern Gulf Islands sont egalement proposees, pour ceux qui desirent decouvrir la splendide nature de la cote ouest du Canada. Ce guide agremente de nombreuses photographies en couleurs s'attarde particulierement a la vie culturelle de Vancouver, Victoria et Whistler, et offre une selection etendue de restaurants, d'hotels, de bars et de boutiques pour tous les gouts et tous les budgets. Une vingtaine de cartes et plans de ville sont proposes, pour mieux vous reperer dans cette superbe region du Canada.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.258 | 0.150 |
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".