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Record W3013225265 · doi:10.4000/pipss.5566

Interview with Colonel Vladimir Furtună, Conducted in Chișinău, Moldova, May 2015 (RU)

2019· article· en· W3013225265 on OpenAlexaff
Ben McVicker

Bibliographic record

VenueThe Journal of power institutions in post-soviet societies · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and environmental studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOfficerPoliticsAncient historyRest (music)MedicineManagementPolitical scienceLawHistoryInternal medicine

Abstract

fetched live from OpenAlex

Vladimir Furtună (b. 1959) was born in the village of Chetrosu in the Drochia district of Moldova. He was an officer (trained as political officer) sent to Afghanistan as the commander of a tank platoon in October 1987 and left with the rest of the 40th Army in February 1989. At the time of the interview Furtună was a colonel teaching at the Alexandru cel Bun Military Academy of Moldova.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0020.000

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 head0.025
GPT teacher head0.247
Teacher spread0.222 · 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.

Study designObservational
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
Published2019
Admission routes1
Has abstractyes

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