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Record W4313399600 · doi:10.18174/571653

Op weg naar grondgebonden rundveehouderij : Verkenning van de beleidsopgave en de effecten van mogelijk toekomstig mestbeleid op areaalbehoefte en -beschikbaarheid, inkomens en continuiteitsperspectieven in de Nederlandse veehouderij

2022· report· nl· W4313399600 on OpenAlexaff
Tanja de Koeijer, P.W. Blokland, Co Daatselaar, J.F.M. Helming, H.H. Luesink, Linda Puister

Bibliographic record

Venuenot available
Typereport
Languagenl
FieldEnvironmental Science
TopicEnvironmental Conservation and Management
Canadian institutionsImpact
Fundersnot available
KeywordsChristian ministryLivestockAgricultural scienceAgricultureGeographyParliamentAgricultural economicsWelfare economicsEconomicsPolitical scienceForestryEnvironmental science

Abstract

fetched live from OpenAlex

The Ministry of Agriculture, Nature and Food Safety (LNV) asked Wageningen Economic Research to explore the policy challenges and economic effects of various scenarios regarding the implementation of track 1 'land-dependent cattle farming' and track 2 'manure processing on farms without land-dependent requirements' of the future manure policy as specified in the LNV letter to the Lower House of Parliament dated 13 April 2021. The study shows that the distribution of livestock farms in terms of economic continuity perspective remains virtually the same for almost all livestock sectors in the scenarios calculated and given the assumptions used. This does not apply to pig farming. Here the income effects are larger and the share of farms in the class 'sufficient economic continuity perspective' clearly decreases. Depending on the scenario, this decrease varies from less than 1 to over 5 percentage points. The extent of the policy challenge has been explored in particular with regard to the availability of sufficient land for the realisation of land-based dairy and cattle farming.

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)0.007
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 categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.448
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0030.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0340.001

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 head0.009
GPT teacher head0.249
Teacher spread0.240 · 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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