MétaCan
Menu
Back to cohort

Arithmetic in Sixteenth-Century Muscovy

2015· article· en· W2731526532 on OpenAlexvenueno aff
Mark A. Tsayger, Rem Aleksandrovich Simonov, Michael Weiss

Bibliographic record

VenueAestimatio Sources and Studies in the History of Science · 2015
Typearticle
Languageen
FieldMathematics
TopicHistory and Theory of Mathematics
Canadian institutionsnot available
Fundersnot available
KeywordsArithmeticMathematicsComputer science

Abstract

fetched live from OpenAlex

Arithmetic in Sixteenth-Century Muscovy by Mark Tsayger is dedicated to an important, complicated, and open research topic in the history of Russian mathematics-the soshny fractions.2 I recall how, at one of the meetings of the Seminar on the History of Mathematics and Mechanics at Moscow State University, one well-known and respected scholar, an expert in this area and one of the presenters at the seminar, Professor Adolf Yushkevich , observed that the system of fractions obtained by successive divisions by two of fourths (chets) and thirds (trets) merits its own special research.Thus, it is without a doubt that Tsayger's recent work into this area is of substantial interest.Yushkevich, in his fundamental book on the history of mathematics in Russia [1968, 16], wrote:1 This review was originally published in Russian in Mathematics in Higher Education 8 (2010) 135-142, a publication of Nizhny Novgorod University of the Russian Federation.The translator acknowledges the support of the Algebraic Geometry Laboratory GU-HSE grant RF Government ag.11 11.G34.31.0023 during the preparation of this translation.2 MW: the adjective 'soshny' in Russian refers to the tax unit, the sokha, corresponding to a variable amount of tilled land in 16th-century Moscow.In the existing literature, 'sokha' has been translated as 'plough'.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.005
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
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 head0.178
GPT teacher head0.355
Teacher spread0.176 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueAestimatio Sources and Studies in the History of ScienceSame topicHistory and Theory of MathematicsFrench-language works237,207