Bibliographic record
Abstract
L'Amerique du Nord a moto ? 50 itineraires de reve vous fera voyager des la premiere page. Ce magnifique album se presente comme une splendide source d'inspiration et une boite a outils pour imaginer et preparer votre prochain road trip sur les plus belles routes a sillonner a moto au Canada et aux Etats-Unis. Ce livre abondamment illustre de photographies plus spectaculaires les unes que les autres vous invite a parcourir de veritables routes de reve pour les motocyclistes, telles les legendaires Route 66 aux Etats-Unis et Transcanadienne au Canada, mais aussi la Million Dollar Highway du Colorado, l'eblouissante Icefields Parkway dans les Rocheuses canadiennes, le Cabot Trail en Nouvelle-Ecosse, la Pacific Coast Highway en Californie et la mythique Blue Ridge Parkway en Virginie et en Caroline du Nord, pour n'en nommer que quelques-unes. Tout au long de ces itineraires de reve, les auteurs rappellent l'existence de grands rassemblements de motocyclistes, qu'il s'agisse de la Bike Week et du Biketoberfest de Daytona Beach ou du Sturgis Motocycle Rally dans le Dakota du Sud. L'Amerique du Nord a moto ? 50 itineraires de reve decrit au jour le jour chaque itineraire, les particularites de chaque route empruntee, les villes et villages a explorer et les paysages a admirer. Il presente aussi pour chaque parcours les coups de c?ur personnels de nos auteurs, leurs meilleurs conseils et recommandations pour reussir vos excursions et des capsules mettant en lumiere les experiences inoubliables a vivre au cours de chaque itineraire. Offrez ou offrez-vous l'Amerique du Nord a moto avec ce livre epoustouflant!
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.122 | 0.014 |
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".