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Record W2330153610 · doi:10.5455/aim.2016.24.149-149

The Most Influential Scientist in the Development of Medical informatics (11): David B. Shires

2016· review· en· W2330153610 on OpenAlexaboutno aff
Izet Mašić

Bibliographic record

VenueActa Informatica Medica · 2016
Typereview
Languageen
FieldHealth Professions
TopicMedical Coding and Health Information
Canadian institutionsnot available
Fundersnot available
KeywordsEngineering

Abstract

fetched live from OpenAlex

David B. Shires (1931–2011) David Shires was Professor of Family Medicine and Community Health and Epidemiology at Dalhouaie University, Canada (1-3). Dr. Shires has practiced medicine in Africa, United Kingdom and United States and has been a resident in Canada for the past 20 years. His early work includes development of a computerized medical record system for the Apollo astronauts. Dr. Shires was elected President of the International Medical lnformatics Association (IMIA) in 1980, and holds Honorary Fellowship, in IMIA as well as the British Computer Society. In 1983 in Paris, he received the Silver Core award for meritorious services to international computing by the International Federation for Information Processing (IFIP). In 1974 he published a book on Computer Technology called “Computer Technology in the Health Sciences” and in 1986 he co-authored “Family Medicine: A Guidebook for Practitioners of the Art”. David B. Shires assumed the IMIA presidency in 1980, one year after the transition from TC4. During his term (1980-1983), Shires reached agreements with the regional group for Central and South America, known as IMIA-LAC (Latin American Countries), and the most populous country in the world, the People’s Republic of China (PRC), making them active participating members in IMIA. Shires saw IMIA as a family, within which “the then USSR and Eastern Bloc countries as well as other countries such as Cuba, could indulge in animated and mutually productive discussions with their western counterparts with each respecting the other’s political differences.” IMIA worked to become meaningful to developing countries and forged new bonds with the World Health Organization. In 1992, Shires reflected that “IMIA has grown considerably in reputation, recognition and credibility in the ten years since I left the presidency, largely due to the continuing hard work of Presidents Peterson, Kaihara and Willams.” Today IMIA reflects Shires’ goal for his presidency in its international constituency, which goes “beyond the Europe–North America-Japan axis to much greater world vision.” Today, the IMIA family includes a newly invigorated African region (HELINA) and is well on its way to facilitating the establishment of a Middle East Region. (MedInfo 1983: Amsterdam, The Netherlands).

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)0.008
metaresearch head score (Gemma)0.021
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: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0020.003
Scholarly communication0.0070.005
Open science0.0010.003
Research integrity0.0040.010
Insufficient payload (model declined to judge)0.0140.012

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 head0.204
GPT teacher head0.499
Teacher spread0.295 · 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
GenreReview

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
Published2016
Admission routes1
Has abstractyes

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