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Record W3012350886 · doi:10.17816/ecogen19140

N.I. Vavilov, VIR, university

2020· article· en· W3012350886 on OpenAlexfundno aff
С. Г. Инге-Вечтомов

Bibliographic record

VenueEcological genetics · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNutrition, Genetics, and Disease
Canadian institutionsnot available
FundersInstitute of Genetics
KeywordsBiological sciencesBiologyBiotechnology

Abstract

fetched live from OpenAlex

Contacts between N.I. Vavilov (VIR) and Yu.A. Filipchenko (Dept. of Genetics, Leningrad State University) reflect close interaction of science and education in fundamental and applied genetics at the first halve of XX century. This interaction put the basis for the future Institute of Genetics of the USSR Academy of Sciences, the first director of which became N.I. Vavilov at 1933. 1932 by Vavilivs initiative there had been organized Dept. of Plant Genetics in the University under leadership of Karpechenko. Mller and Bridges had been teaching in the University being invited by Vavilov in Institute of Genetics. The revival of genetics in the University at 50-s of XX century, after lysenkoism period, proceeded under the influence of Vavilov even perished 1943 in prison. The role of Lobashev and Feodorov in those events is evident.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.672
Threshold uncertainty score0.561

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.212
Teacher spread0.195 · 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 teacher head, 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
Published2020
Admission routes1
Has abstractyes

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