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Record W2354251807

Problems and strategies of map of China in scientific journals

2015· article· en· W2354251807 on OpenAlex
Lin Luo

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBianji xuebao · 2015
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Computational Techniques and Applications
Canadian institutionsScience North
Fundersnot available
KeywordsChinaSafeguardingQuality (philosophy)Political scienceOperations researchData scienceComputer scienceLawEngineeringMedicineEpistemology
DOInot available

Abstract

fetched live from OpenAlex

Illustrations are the important and indispensable part of scientific journal. Map of China is one of the representative and common map in scientific articles. Besides the criterion and science,more attention should be paid to the political issues that may damage the benefit of China. Main problems in the scientific journals can be categorized as territory loss,boundary error,Hong Kong,Macau and Taiwan related errors. Then,we analyze the reasons for these problems and propose the strategies and suggestions for authors. Meanwhile,we put forward some proposals for authors,editors and administrators of scientific journals and expect joint efforts from them to guarantee that the map of China is drawn correctly,which is of significance for improving the publication quality of scientific journals, and safeguarding national interest.

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.

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)0.000
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.791
Threshold uncertainty score0.167

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.063
GPT teacher head0.324
Teacher spread0.261 · 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