Bibliographic record
Abstract
Introduction. VENICE -- THE CLASSIC CASE STUDY. ARRIVING IN THE CITY. Gardermoen Airport, Oslo, Norway. The New TGV Mediterranee Stations, France. Chep Lap Kok Airport, Hong Kong. Translink Interchange, Bangor/Belfast, Northern Ireland. Nils Ericson Bus Station, Gothenburg, Sweden. Grand Central Station, New York, USA. Yokohama Ferry Terminal, Japan. Salamanca Train Station, Spain. ENJOYING THE CITY. Marbella Old Town, Spain. The South Bank, Brisbane, Australia. Copenhagen Squares and Spaces, Denmark. Faneuil Hall Marketplace, Boston, USA. Toronto Malls, Canada. Wall Murals, South Africa. New Rondas, New Ramblas, Barcelona, Spain. Circular Quay and The Rocks, Sydney, Australia. Vancouver Downtown, Canada. Public Realm, Glasgow, Scotland. Post Office Park, Boston, USA. GETTING AROUND THE CITY. Edinburgh's Greenways, Scotland. Bristol -- The Legible City, England. Cycling in Rennes, France and Groningen, The Netherlands. Curitiba, Brazil. The Strasbourg LRT, France. The Portland Streetcar, Oregon, USA. The Brisbane Busway, Australia. Singapore Road Pricing, Singapore. The ULTra System, Cardiff, Wales. CONCLUSION. URBAN HEROS. BIBLIOGRAPHY, USEFUL WEBSITES, PHOTO CREDITS.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.084 | 0.028 |
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".