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Record W4312740603 · doi:10.35992/pdm.v1i2.338

Design of an integral model to manage social interest housing construction projects with emphasis in socio-environmental variables in family compensation boxes

2019· article· en· W4312740603 on OpenAlexaff

Bibliographic record

VenueProject Design and Management · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBusiness, Innovation, and Economy
Canadian institutionsImpact
Fundersnot available
KeywordsLeverage (statistics)BusinessEconomic growthEconomicsComputer science

Abstract

fetched live from OpenAlex

At present, the construction sector has an important weight within the trade world economy, in the last decadetheconstruction has had a higher growth than otherseconomicsaspects of the nations, different countries have chosen to increase and improve their processes of housing construction.In Colombia, it has been identified that construction encourages at least 32 sectors of the economy, being one of the main actors in the economic leverage of the nation; in which resources are mobilized, jobs are usedand the level of quality of life ismoreimproved. However, social interest housing construction projects (VIS) face various problems throughout their life cycle, due to the large part that there is notspecialized model that allows the monitoring of the project in each of its stages and that consider the project as a global aspect, it is for this reason that it is proposed within this study the formulation of a model that establishes clear principles under international guidelines and that meet, among other things, the main objectives of the project without set aside socio-environmental variables, thus giving a powerful and very solid tool for project managers, generating value and knowledge for project management.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.538
Threshold uncertainty score0.705

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.074
GPT teacher head0.231
Teacher spread0.156 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2019
Admission routes1
Has abstractyes

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