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Record W4285216870 · doi:10.18174/569857

Mogelijke inkomenseffecten van de oorlog in Oekraïne voor bedrijven in het Nederlandse viscluster : Een eerste verkenning

2022· report· nl· W4285216870 on OpenAlexaff
B. Deetman, J.A.E. van Oostenbrugge, Geert Hoekstra, A. Klok

Bibliographic record

Venuenot available
Typereport
Languagenl
FieldEnvironmental Science
TopicEnvironmental and Biological Research in Conflict Zones
Canadian institutionsImpact
Fundersnot available
KeywordsAgricultureSanctionsYield (engineering)Political scienceBusinessEconomyAgricultural economicsAgricultural scienceEconomicsGeographyEnvironmental scienceArchaeology

Abstract

fetched live from OpenAlex

De oorlog in Oekrane en daarmee samenhangende sancties hebben gevolgen voor de kosten van landbouwen visserijproductie en voor de opbrengstprijzen van landbouw-en visserijproducten. Er is bij overheid en bedrijfsleven behoefte aan een inschatting van de effecten hiervan op de inkomens van de ondernemers in de agrarische sector. Deze studie geeft een eerste voorlopige inventarisatie van de mogelijke effecten voor de visserij op de korte termijn.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.210
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0930.002

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 head0.036
GPT teacher head0.301
Teacher spread0.265 · 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 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

Citations2
Published2022
Admission routes1
Has abstractyes

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