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Record W1515265090

Inventing diagnosis: Theophilus' De urinis in the classroom.

2000· article· en· W1515265090 on OpenAlexafffund
Faith Wallis

Bibliographic record

VenuePubMed · 2000
Typearticle
Languageen
FieldArts and Humanities
TopicHistory of Medicine Studies
Canadian institutionsMcGill University
FundersAssociated Medical Services
KeywordsSign (mathematics)Context (archaeology)State (computer science)EpistemologyPhilosophyHistoryComputer scienceArchaeology
DOInot available

Abstract

fetched live from OpenAlex

This paper shows how the two earliest Latin expositions of Theophilus' De urinis understood diagnosis in different ways. The "Chartres" commentator sees urine as a sign of physiological process and something which is derived from a disease state. By contrast, the Digby commentator is more concerned with how uroscopy functions at the bedside as a tool that enables us to infer disease states from urine. Though they understand the role of diagnosis differently, both commentaries reflect the new intellectual context of twelfth century medicine, where physical signs cease to be mere prognostic omens, and become tools for attaining knowledge of processes otherwise inaccessible to the senses.

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)0.004
metaresearch head score (Gemma)0.009
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 score0.992
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.023
Scholarly communication0.0050.010
Open science0.0010.003
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0040.001

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 head0.043
GPT teacher head0.205
Teacher spread0.162 · 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

Citations13
Published2000
Admission routes2
Has abstractyes

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