DESA1002 'Nine Quarter City' - <Yi Chen Lin>
Bibliographic record
Abstract
In this semester my given city is Venice. The first concept that came across my mind is building a public servise building such as hospital, police station or fire station. After analyzing the location of my building, I choose to start from the corner facing the main canal. Building a fire station is my final decision, I tried to analyse all the functions needed as a fire station. It includes fireboat dock, reception, emergency space, office, bedrooms, toilet and shower, common room and recreation area. At the beginning stage I tried to separate the building into two part: private and public area. I tried to build a concrete block contains fireboat dock and bedrooms on the top. This is also the main structure system. After revising all the floor plans, the final building is supported by five reinforced concrete columns and slabs holds up each floor. Unlike first semester all the ideas were simply from my creation and imagination, this project is conducted under constant revising and checking all the factors such as building orientation, neighbor’s building type, traffic circulation and structure system. I learnt to develop a systematic, programmatic way to analyse the building, from its function, location, structure to cladding.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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; both teacher heads agree on what is shown here.
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".