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Record W2232326311 · doi:10.12775/sz.2015.08

Vitae medicorum Gedanensium – rękopis z połowy XVIII w. ze zbiorów Biblioteki Gdańskiej Polskiej Akademii Nauk

2015· article· pl· W2232326311 on OpenAlexaboutno aff
Bartłomiej Siek, Adam Szarszewski

Bibliographic record

VenueStudia Źródłoznawcze Commentationes · 2015
Typearticle
Languagepl
FieldArts and Humanities
TopicHistorical and Cultural Studies of Poland
Canadian institutionsnot available
Fundersnot available
KeywordsHandwritingQuarter (Canadian coin)ArtHistoryClassicsArchaeology

Abstract

fetched live from OpenAlex

Vitae medicorumGedanensium – a Manuscript from the Mid–eighteenth Century in the Collections of the Gdańsk Library of the Polish Academy of SciencesOne of the most interesting archival sources for the history of medicine in Gdańsk is a manuscript in the Gdańsk Library of the Polish Academy of Sciences (Ms514), containing biographies of local physicians. Vitae medicorum Gedanensium, qui tum apudsuos tum apudexteros floruerunt originates from the library of V. Schlieff (1680–1750) and is attributed to the Gdańsk physician L. von Hammen (1651–1689). An analysis of the source, however, leads to the conclusion that this is a copy of the von Hammen manuscript in an unknown handwriting. The handwriting of the numerous later supplements is that of von Hammen, with Schlieff expanding the information in the biogrammes. The dictionary contains data about 82 Gdańsk physicians from the second quarter of the sixteenth century to the early eighteenth century, arranged in chronological order, and was not completed due to the death of the author. This is a valuable contribution to the history of medicine in Gdańsk, in particular after it was supplemented by Schlieff, who benefitted from a more copious range of sources than the one at the disposal of his predecessor.

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)0.001
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 score0.015
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0050.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0150.006

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 head0.108
GPT teacher head0.286
Teacher spread0.179 · 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
Published2015
Admission routes1
Has abstractyes

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