Tokyo Fish-Eye. Développement du pôle Waterfront-Subcenter. Relocalisation du marché de gros de poisson Tsukiji
Bibliographic record
Abstract
In the most populous metropolis, the world's largest fish wholesale market, the Tsukiji market, needs to expand. Land is too expensive to afford, but a quarter of the central districts remain underused. Relocate the fish market! Having reached its geographical limits, Tokyo has expanded on the sea. The strip of reclaimed land dividing the central wards from the sea is called the Tokyo Bay Area. Left out from the tight network of public transportation, it remains disconnected and difficult to access. No real focal point has yet taken root in the Bay. In order to ignite its development into a true sub-centre, the Bay needs a vibrant attractor. Tsukiji, the world's biggest fish wholesale market has reached the limits of its development on the present site and plans to move. With its huge daily flow of people and vehicles, the wholesale market and the neighbouring outer market are one of Tokyo's busiest and most popular attractors. The project relocates the fish market on Odaiba Island and lays out a masterplan for the entire site. A new subway line is planned in addition to the existing Rinkai line. The new market infrastructure is a large roof serving as a shelter for three functions: the actual wholesale market with its stalls, auction halls and docks, the metro station which serves as entrance hall for the market and the so-called outer market.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.542 | 0.252 |
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".