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Record W7023944119

Post-evaluation of development projects for the transformation of public spaces

2024· dissertation· en· W7023944119 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueElectronic Archive of Ural Federal University (ELAR UrFU) · 2024
Typedissertation
Languageen
FieldEngineering
TopicReal estate and construction management
Canadian institutionsnot available
Fundersnot available
KeywordsNoveltyDevelopment (topology)Quarter (Canadian coin)Transformation processesScientific development
DOInot available

Abstract

fetched live from OpenAlex

The master's thesis consists of an introduction, three chapters, a conclusion and a bibliography. The paper examines the methodology of post-assessment of a development project for public spaces using the example of the Starogorodetsky Quarter improvement project in Belebey, Republic of Bashkortostan. The paper substantiates the hypothesis of the positive effects of using post-construction assessment in the implementation of development projects for public spaces using scientific methods; presents the results of applying the post-assessment methodology to a real object; and postulates conclusions about the need to apply this methodology in the implementation of development projects. The conclusion summarizes the results of the study, formulates the general findings of the study, scientific novelty and scientific result.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.767
Threshold uncertainty score0.565

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.220
Teacher spread0.205 · 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