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Record W2604465081 · doi:10.1136/bmj.j1603

Peter Gordon Watson

2017· article· en· W2604465081 on OpenAlexaboutno aff
Andrew Hill Watson

Bibliographic record

VenueBMJ · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicHistory of Medicine Studies
Canadian institutionsnot available
Fundersnot available
KeywordsWatsonComputer scienceData scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Peter Gordon Watson was born in Newport, Monmouth, where his parents were running a free mobile medical clinic during the great depression. After national service as a subaltern in the Royal Horse Artillery, he read natural sciences at Queens’ College, Cambridge, before his clinical studies at University College Hospital, London. He trained in ophthalmology at University College Hospital, Moorfields Eye Hospital, and the Institute of Ophthalmology, and he eventually became senior lecturer to Professor Barrie Jones at Moorfields. He was encouraged to set up a scleritis clinic there, which he ran as an honorary consultant from 1970 to 1995. At the time there was effectively no treatment for scleral inflammation, and no one knew how the disease developed, which varieties were dangerous and sight threatening, and which were benign and needed no treatment at all. The clinic soon attracted patients from around the world. The …

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)0.002
metaresearch head score (Gemma)0.011
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: Empirical · Consensus signal: none
Teacher disagreement score0.076
Threshold uncertainty score0.253

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0760.031

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 head0.077
GPT teacher head0.303
Teacher spread0.226 · 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
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

Citations1
Published2017
Admission routes1
Has abstractyes

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Same venueBMJSame topicHistory of Medicine StudiesFrench-language works237,207