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Record W4380151277 · doi:10.23977/aetp.2023.070416

Considerations on the Scientific Research Work of Application-Oriented Undergraduate Universities in the First-Class Construction

2023· article· en· W4380151277 on OpenAlexvenueno aff

Bibliographic record

VenueAdvances in Educational Technology and Psychology · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicEducational Reforms and Innovations
Canadian institutionsnot available
FundersJinling Institute of Technology
KeywordsConstructiveTask (project management)Work (physics)Class (philosophy)IncentiveQuality (philosophy)Engineering managementEngineering ethicsEngineeringMathematics educationComputer sciencePsychologyProcess (computing)Mechanical engineering

Abstract

fetched live from OpenAlex

Cultivation of high-quality application-oriented talents is the main task of application-oriented undergraduate universities. Scientific research work is very important for application-oriented undergraduate universities. It can promote the overall teaching ability level and the quality of application-oriented talent cultivation and is also an important task in the construction of first-class application-oriented undergraduate universities. Application-oriented undergraduate universities should improve the level of scientific research work by adjusting the teaching staff structure, building scientific research platforms, implementing research incentive policies and strengthening deep cooperation between universities and enterprises. Only through these constructive measures can an application-oriented university better serve the local economic and social development and improve the quality of application-oriented talent cultivation.

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)0.019
metaresearch head score (Gemma)0.024
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 score0.019
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0090.006
Scholarly communication0.0130.003
Open science0.0020.005
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0090.002

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 head0.028
GPT teacher head0.365
Teacher spread0.337 · 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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