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Record W6981329161

Edificio de Usos Mixtos de Difusión Cultural y Formación Inmediata en el Distrito de La Victoria

2023· dissertation· es· W6981329161 on OpenAlexaboutno aff

Bibliographic record

Venuerenati · 2023
Typedissertation
Languagees
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsnot available
Fundersnot available
KeywordsMetropolitan areaPopulationContext (archaeology)Quarter (Canadian coin)
DOInot available

Abstract

fetched live from OpenAlex

La presente tesis muestra el análisis y estudio del distrito de La Victoria el cual propone un proyecto que responde al crecimiento \ndesmedido del comercio, a la falta de infraestructura y demanda educativa existente, y a la falta de zonas de recreación, formación y difusión \ncultural. \nLa Victoria presenta el desarrollo comercial más grande de Lima como una gran diversidad cultural siendo conformado en su mayoría por \nmigrantes del interior del país, sin embargo, su característica de “distrito comercial” ha limitado y desplazado el desarrollo de infraestructura \neducativa y cultural. \nCabe agregar que el proyecto se encuentra ubicado en la avenida Miguel Grau, una avenida que actualmente está pasando por un proceso \nde transformación buscando la revalorización e integración del distrito de la Victoria como de Cercado de Lima. \nPor ende, debido a todo lo expuesto anteriormente, se planteó un proyecto de usos mixtos el cual mantendría el carácter comercial del \ndistrito y de la avenida Grau, cubriría una demanda educativa existente brindando espacios adecuados de acuerdo al carreras demandadas y se \nbrindaría un espacio para la formación y difusión de las artes que se practican en distrito generando así una mejor integración entre ambos \ndistritos, revalorizando el entorno del proyecto y brindando un proyecto multifuncional

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.269
Threshold uncertainty score0.535

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.002
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.033
GPT teacher head0.472
Teacher spread0.439 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2023
Admission routes1
Has abstractyes

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