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Record W2736406285

Plan de negocio dirigido a la recuperación de neumáticos usados y comercialización de grano de caucho reciclado (GCR) en la ciudad de Bogotá

2016· dissertation· es· W2736406285 on OpenAlexaboutno aff
María Isabel Mesa Trujillo, Samuel Patarroyo Díaz

Bibliographic record

Venuenot available
Typedissertation
Languagees
FieldHealth Professions
TopicOccupational Health and Safety in Workplaces
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessAbandonment (legal)Business planGeneral partnershipWelfare economicsPolitical scienceEconomicsMarketingFinance
DOInot available

Abstract

fetched live from OpenAlex

The project to be raised largely seeks to resolve the problem that currently exists in the streets of major cities of the country, due to the abandonment of tires that are no longer used by consumers and also to intervene in the public space that affects the environment and society in general. The business idea raised is the creation of a company that is dedicated to the transformation of the tires that are collected, for subsequent marketing and sale as raw material mainly for the construction sector. The objective is to be achieved by generating partnership with the national government and local mayors Reuse of used tires It is principal raw material in the construction sector, such as for the production of asphalt pavement, based on the recognized success of its implementation in countries like Canada, the US and Spain, among others, is a breakthrough technological, cultural and environmental benefits to the country and society.

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)0.007
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.030
GPT teacher head0.413
Teacher spread0.383 · 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 designObservational
Domainnot available
GenreEmpirical

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
Published2016
Admission routes1
Has abstractyes

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