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Record W2328286940 · doi:10.1227/neu.0b013e318232328c

Maister Peter Lowe and His 16th Century Contributions to Cranial Surgery

2011· article· en· W2328286940 on OpenAlexaff
R. Shane Tubbs, Martin M. Mortazavi, Mohammadali M. Shoja, Marios Loukas, Aaron Cohen‐Gadol

Bibliographic record

VenueNeurosurgery · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicHistory of Medicine Studies
Canadian institutionsPediatric Oncology Group
Fundersnot available
KeywordsMedicineNeurosurgerySkullClassicsSurgeryGeneral surgeryHistory

Abstract

fetched live from OpenAlex

Before the advent of neurosurgery as a discipline, various historic surgeons performed procedures on the skull and brain. One early pioneer of surgery, Peter Lowe (c. 1550-1612), not only wrote of methods of cranial surgery in his Chirurgerie, which was the first comprehensive text of surgery written in English, but also founded what would become the Royal Faculty of Physicians and Surgeons. Included in the powers given to him by King James VI was the authority to regulate the practices of medicine, surgery, and pharmacy in the west of Scotland. This 16th century Scottish surgeon trained in Paris, where he was influenced by Ambroise Paré and wrote about the "Spanish sickness." In his surgical text, Lowe wrote about his methods of multiple neurosurgical procedures. The present study discusses the life of Maister Peter Lowe and reviews his contributions to what became the art of neurosurgery.

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)0.001
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0070.013
Scholarly communication0.0040.003
Open science0.0000.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.048
GPT teacher head0.228
Teacher spread0.181 · 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

Citations7
Published2011
Admission routes1
Has abstractyes

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