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Record W6980973386

DESA1002 'Nine Quarter City' - <Van Khanh Phan>

2020· other· en· W6980973386 on OpenAlexaboutno aff

Bibliographic record

VenueThe Sydney eScholarship Repository (The University of Sydney) · 2020
Typeother
Languageen
FieldBusiness, Management and Accounting
TopicSharing Economy and Platforms
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)RoofNiceTerrace (agriculture)Variety (cybernetics)Front (military)
DOInot available

Abstract

fetched live from OpenAlex

\tThe idea of designing a hotel in Venice was decided due to the fame of this city, so many tourists want to visit this city at least once. Therefore, each unforgettable moment living in a nice hotel is very important. \tThe most interesting feature of my building is the changing direction part. My building has two different parts, one is quite ‘static’ and one is quite ‘dynamic’. With the ‘dynamic’ part, each level of the building has its own direction, consequently, tourists can have many different views from different angles, and if someone did live on the level 1, they would really want to come back and try the room on other levels. Moreover, the changing direction idea also represents the variety of canals in this city. \tIn addition, tourists can easily recognise this hotel due to the shape of the roof. Roof of this hotel includes many triangles pieces of glass combined with steel frame. The breaking down one big roof into many smaller roofs with many different angles provides various and nice views for tourists at night when the dinner is served in a small restaurant on the top floor. Roof top is not only the terrace but also the beautiful place for tourists to have a nice dinner with very beautiful sky with plenty of stars above. \tMoreover, this hotel has one side facing to the Grand Canal, and this side is one side of the changing direction part as well. The multidirectional part includes levels that jut out directly to the canal; therefore, it provides the floating feeling for tourists living here. \tThe location of this hotel is also nice; one side is canal, other sides are roads, consequently, it is easier to find this hotel in a very beautiful city like Venice. Welcome to Venice Hotel

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.289
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.002

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.

Opus teacher head0.016
GPT teacher head0.177
Teacher spread0.161 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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