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The handwritten legacy of N.E Katanov in the funds of Russian archives: diaries and materials from the period of travel to Siberia and Xinjiang (1889-1892): To the 160<sup>th</sup> anniversary of his birth

2022· article· en· W4298064333 on OpenAlexaboutno aff
R. M. Valeev, R. Z. Valeeva, Valentina N. Tuguzhekova

Bibliographic record

VenueOrientalistica · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Culture and Media Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBiographyScholarshipPeriod (music)Quarter (Canadian coin)HumanismContext (archaeology)PoliticsHistoryState (computer science)Oriental studiesIron CurtainAncient historyClassicsPolitical scienceCold warArt historyArtLawArchaeologyAesthetics

Abstract

fetched live from OpenAlex

Professor N.F. Katanov (1862-1922) is one of the outstanding national scholars, representatives of Russian scholarship, education and culture of the 19th-20th centuries. His life’s journey and legacy reflected important events and trends in domestic and world oriental studies and Turkic studies. Stages of his biography and a huge creative heritage are interesting and outstanding, instructive and tragic at the same time. He became the personification of two worlds in Russia - European and Asian. The biography and heritage of N.F. Katanov are of academic and especially scientific and educational, humanistic interest. His life and works should not be perceived only in the system of coordinates of the history of Russian and European oriental studies. It is necessary to take into account the broad socio-political and socio-cultural context of the development of Oriental studies, including Turkic studies, as well as Russian society and the state in the second half of the 19th - the first quarter of the 20th century.

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)0.002
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: Other · Consensus signal: Other
Teacher disagreement score0.018
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0030.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0180.006

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 head0.012
GPT teacher head0.248
Teacher spread0.236 · 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
GenreOther

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
Published2022
Admission routes1
Has abstractyes

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