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Record W4415762499 · doi:10.29011/2575-9760.011475

Avicenna’s Canon of Medicine: Foundations of Plastic and Reconstructive Techniques

2025· article· W4415762499 on OpenAlexaff

Bibliographic record

VenueJournal of Surgery · 2025
Typearticle
Language
FieldArts and Humanities
TopicHistory of Medicine Studies
Canadian institutionsToronto Rehabilitation Institute
Fundersnot available
KeywordsCanonGeorge (robot)Face (sociological concept)Ideal (ethics)

Abstract

fetched live from OpenAlex

Avicenna (Ibn Sina, 980-1037 CE) is remembered as one of the greatest minds in medical history.His massive text, The Canon of Medicine (Al-Qanun fil-Tibb), guided physicians for centuries and continues to inspire physicians and surgeons today.While most people know him for his philosophical and scientific insights, Avicenna also described surgical ideas that connect closely with modern plastic and reconstructive surgery.In his writings, he outlined methods of eyelid surgery, carpal tunnel release, tracheostomy, nerve repair, cleft surgery, fracture treatment, and wound care.He also detailed salient points about anesthesia, sterilization, and organized surgical wards-concepts far ahead of his time.This paper looks at how Avicenna's ideas shaped the development of modern plastic and reconstructive surgery and how his clinical observations still relate to contemporary practice.His seminal work shows that curiosity, compassion, and the attention to detail were forming the developing field of surgery over a thousand years ago.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.996
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0040.016
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0060.001

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 head0.046
GPT teacher head0.284
Teacher spread0.239 · 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
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
Published2025
Admission routes1
Has abstractyes

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