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Record W4395956073 · doi:10.18280/ijsdp.190431

Developing Science, Technology, and Innovative Creativity to Meet the Requirements of Sustainable Development in Vietnam: Current Situation and Solutions

2024· article· en· W4395956073 on OpenAlexvenueno aff
Nguyễn Minh Trí, Le Thanh Hoa

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2024
Typearticle
Languageen
FieldComputer Science
TopicEngineering Education and Technology
Canadian institutionsnot available
Fundersnot available
KeywordsCreativityCurrent (fluid)Sustainable developmentEngineering ethicsEngineeringEngineering managementPolitical scienceElectrical engineering

Abstract

fetched live from OpenAlex

In conjunction with labor, capital, and natural resources, the pivotal role of science, technology, and innovation in the socioeconomic advancement of nations and societies is indisputable.This domain has historically been instrumental in propelling societal advancement, augmenting the standard of living, and fortifying national security.Nonetheless, the prevailing scenario evinces myriad challenges confronting science, technology, and innovation, particularly amidst the epoch of the Fourth Industrial Revolution.To harness the full potential of science, technology, and innovation, holistic strategies must be devised and implemented.The objective is to fulfill the requisites of sustainable socioeconomic progress, particularly amidst the pervasive impact of the Fourth Industrial Revolution across all facets of societal existence.Research endeavors will be directed towards scrutinizing and appraising the current landscape, alongside offering recommendations and remedies to foster the sustainable evolution of science-technology, innovation, and sustainable development in Vietnam.

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)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.031
GPT teacher head0.322
Teacher spread0.291 · 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
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

Citations1
Published2024
Admission routes1
Has abstractyes

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