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Record W7126330016

Hvorfor kæmper så mange canadiere for Ukraine?

2022· other· da· W7126330016 on OpenAlexaboutno aff
Uffe Østergaard

Bibliographic record

VenueCBS Research Portal (Copenhagen Business School) · 2022
Typeother
Languageda
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsMangePublic healthAnimal health
DOInot available

Abstract

fetched live from OpenAlex

Historisk set. Mange af de frivillige, der kæmper på ukrainsk side mod Rusland, kommer fra Canada, som huser et af de største ukrainske mindretal i verden.

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)0.013
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.602
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.014
Meta-epidemiology (narrow)0.0040.004
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0060.013
Science and technology studies0.0050.002
Scholarly communication0.0030.002
Open science0.0090.005
Research integrity0.0020.007
Insufficient payload (model declined to judge)0.9140.312

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 head0.119
GPT teacher head0.391
Teacher spread0.272 · 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; both teacher heads agree on what is shown here.

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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