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Record W3210894172

THE LINGUISTIC ASPECT OF MEDICAL RESEARCH PAPERS- NEED TO DEVELOP INSIGHT

2008· article· en· W3210894172 on OpenAlexaff
Amin A. Muhammad Gadit

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiomedical Text Mining and Ontologies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsLinguisticsComputer scienceValue (mathematics)UrduOrder (exchange)English languageInternational communicationMedical educationPsychologyMedicineBusinessCommunication
DOInot available

Abstract

fetched live from OpenAlex

All indexed biomedical journals are required to conform to the international standards and to follow the pattern as suggested by the guidelines for indexed medical journals1. The main language of communication for medical literature is 'English' though there are a number of indexed journals published in different languages. Our national language 'Urdu' has not progressed so far in terms of its medical literature value that we can adopt this for research communications. Moreover, the medium of medical teaching in the country is 'English' language. Hence, it is expected internationally that we can communicate as efficiently in this language as any other English speaking country in order to make our research findings more understandable and transmissible.

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)0.076
metaresearch head score (Gemma)0.201
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.924
Threshold uncertainty score0.399

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0760.201
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0100.010
Science and technology studies0.0030.010
Scholarly communication0.0220.027
Open science0.0020.006
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0080.004

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 head0.327
GPT teacher head0.578
Teacher spread0.251 · 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.

Study designQualitative
DomainReporting
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
Published2008
Admission routes1
Has abstractyes

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