EXAMINATION PROCESS OF MASTER PLAN OF EXPO'70 DESIGNED BY TOMOYA MASUDA
Bibliographic record
Abstract
Banpaku-keikaku is the master plan of Expo'70 designed by Tomoya Masuda & associates. Banpaku-keikaku has following characteristics: 1) Exhibition areas and artificial lake are designed to make a total view of the site. 2)Manipulation of the topography is related to placement of exhibition areas. 3)Viewing of the Expo starts with getting a total view of the site by the transportation. 4)With these elements, Banpaku-keiakaku was designed to achieve an idea called Keikan-ka, which is making a new landscape that has a new meaning. 5)Banpaku-keikaku were designed based on usage of former site. This work is important because concepts of discernment and manipulation of the topography and Keikan-ka which are related to Masuda's thoughts are utilized. Therefore, the author has studied its ideas and characteristics on the preceding paper (2019). Based on that paper, the author aimed to reveal how they developed that ideas and characteristics on this paper. There are two important materials for this aim which are made before completion of Banpaku-keikaku. That are four drafts for Banpaku-keikaku, and examination of the two past exposition, which are Lausanne Expo'64 and Montreal Expo'67 by Tomoya Masuda & associates. The former are included in a unpublished blueprint book 『JEXPO’70 会場計画』,which is discovered by the author, the latter are included in 「万博計画［Ⅰ］」,which is a published articles of Banpaku-keikaku. The author studied these materials.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.058 | 0.012 |
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".