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Record W4226190427 · doi:10.18174/566959

Knelpuntenanalyse conflict Oekraine : analyse knelpunten korte termijn voor de agrarische ketens

2022· report· nl· W4226190427 on OpenAlexaff
Petra Berkhout, Ron Bergevoet, Allard Jellema

Bibliographic record

Venuenot available
Typereport
Languagenl
FieldEconomics, Econometrics and Finance
TopicEconomic Sanctions and International Relations
Canadian institutionsImpact
Fundersnot available
KeywordsMemorandumMemorandum of understandingOperations researchBusinessManagementPolitical scienceEngineeringEconomicsLaw

Abstract

fetched live from OpenAlex

De oorlog in Oekraïne leidt tot diverse knelpunten in de agrarische ketens in Nederland.Deze notitie bevat een eerste analyse van deze knelpunten op basis van een inventarisatie bij het bedrijfsleven en expertkennis.The war in Ukraine has led to various bottlenecks in the agricultural chains in the Netherlands.This memorandum contains a first analysis of these bottlenecks, based on an inventory by the business community and expert knowledge.

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)0.005
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.069
Threshold uncertainty score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0040.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0120.001

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 head0.090
GPT teacher head0.283
Teacher spread0.194 · 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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