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Record W1977274281 · doi:10.2174/187569211794728841

Editorial (Asia-Pacific Health 2020 and Genomics without Borders: Co-Production of Knowledge by Science and Society Partnership for Global Personalized Medicine)

2011· article· en· W1977274281 on OpenAlexafffund
Vural Özdemir, David Handojo Muljono, Tikki Pang, Lynnette R. Ferguson, A. Manamperi, Sofía Samper, Toshiyuki Someya, Anne Marie Tassé, Shih‐Jen Tsai, Hong‐Hao Zhou, Edmund J.D. Lee

Bibliographic record

VenueCurrent pharmacogenomics and personalized medicine (Online)/Current pharmacogenomics and personalized medicine · 2011
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsMcGill University
FundersCanadian Institutes of Health ResearchU.S. Public Health Service
KeywordsGeneral partnershipGenomicsPolitical scienceProduction (economics)Asia pacificGlobal healthPersonalized medicinePublic healthEconomic growthMedicineBusinessGenomeBiologyBioinformaticsGeneticsGeneInternational tradeEconomicsNursing

Abstract

fetched live from OpenAlex

Keywords: Asia-Pacific, genomics and international development, global health, health 2020 policy, knowledge co-production, LMICs, public health genomics, science and society, theragnostics, cultural lags

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)0.009
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.995
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.024
Meta-epidemiology (narrow)0.0050.001
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0040.002
Science and technology studies0.0050.004
Scholarly communication0.0090.006
Open science0.0040.002
Research integrity0.0270.032
Insufficient payload (model declined to judge)0.0130.009

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 head0.104
GPT teacher head0.432
Teacher spread0.327 · 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 designNot applicable
Domainnot available
GenreEditorial

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

Citations19
Published2011
Admission routes2
Has abstractyes

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