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Record W2998553975 · doi:10.5539/ass.v16n1p1

The Foundation of Vietnam and India Relation, Historical Values

2019· article· en· W2998553975 on OpenAlexvenueno aff
Vu Hong Van

Bibliographic record

VenueAsian Social Science · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicVietnamese History and Culture Studies
Canadian institutionsnot available
FundersTrường Đại học Giao thông vận tải
KeywordsFriendshipFoundation (evidence)FeelingState (computer science)Relation (database)Political scienceWifeGender studiesEconomic growthSociologyDevelopment economicsGeographySocial scienceLawSocial psychologyPsychologyEconomics

Abstract

fetched live from OpenAlex

Vietnam and India: Timeless friendship is a common feeling of international friends about Vietnam and India friendship. Cultivated from the 50s of the last century, over time, despite the distance of geography, the relationship is constantly being strengthened and developed. Indian President Ram Nath Kovind’s visit to Vietnam from November 18 - 20, 2016 and his wife once again continued to strengthen that rare friendship. Research on the relationship between Vietnam and India in history as well as in the present will help the two countries understand more about each other, about the values that the predecessors as well as the efforts of the leaders of the two countries in the present. Since then, it is a solid foundation for sustainable development in the future. Based on the studies of ancient documents as well as recent state relations of leaders of the two countries. The article sheds more light on the good relations between the two peoples, the source of good relations at the present time and prospects for future development.

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 score0.058
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.006
Scholarly communication0.0070.002
Open science0.0000.002
Research integrity0.0000.002
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 head0.012
GPT teacher head0.282
Teacher spread0.270 · 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

Citations5
Published2019
Admission routes1
Has abstractyes

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