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Record W2582130596

Producentenorganisaties als instrument voor concurrentiekracht en innovatie : uitbreiding van perspectief door het nieuwe GLB?

2015· article· nl· W2582130596 on OpenAlexaff
A.B. Smit, H. Prins, M.E.G. Litjens, A. van den Ham, J. Bijman, Wim Zaalmink

Bibliographic record

VenueSocio-Environmental Systems Modeling · 2015
Typearticle
Languagenl
FieldBusiness, Management and Accounting
TopicWine Industry and Tourism
Canadian institutionsImpact
Fundersnot available
KeywordsBusinessPosition (finance)Competition (biology)Agricultural sciencePolitical scienceFinance
DOInot available

Abstract

fetched live from OpenAlex

Producer organisations (POs) in agri- and horticulture give primary producers the opportunity to strengthen their position in the chain. Until 1 January 2014, POs were only recognised in the vegetables and fruit sector. Since then, POs can now also be organised in other agri- and horticulture sectors due to a change in EU policy. This refers to officially recognised producer organisations besides or instead of several existing horizontal cooperative organisations. This report presents the opportunities of cooperation in general and of organising a PO in the agri- and horticulture, including competition aspects which could create some barriers.

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)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.006
Scholarly communication0.0150.008
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0150.001

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 head0.042
GPT teacher head0.229
Teacher spread0.187 · 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 designTheoretical or conceptual
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
Published2015
Admission routes1
Has abstractyes

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