MétaCan
Menu
Back to cohort
Record W4385217823 · doi:10.18174/572701

Landbouwstructuur in regio Foodvalley en gemeenten Bunschoten, Leusden, Putten en Woudenberg

2022· report· nl· W4385217823 on OpenAlexaff
G.S. Venema, Ruud van der Meer, Jakob Jager

Bibliographic record

Venuenot available
Typereport
Languagenl
FieldEnergy
TopicEnergy, Environment, Agriculture Analysis
Canadian institutionsImpact
Fundersnot available
KeywordsArt

Abstract

fetched live from OpenAlex

The research was carried out on behalf of the Foodvalley Region, and consists of providing the most up-to-date picture of structural characteristics and socio-economic aspects of the primary agricultural sector in the Foodvalley region, supplemented by the municipalities of Bunschoten, Leusden, Putten and Woudenberg. It also provides insight into developments in recent years. In 2020 there were 2,000 agricultural companies in the study area, mainly dairy cattle, veal calves and other grazing livestock farms. Three-quarters of the 32,000 ha in the area is grassland. Most livestock herds have declined in recent years; for most sectors the livestock density per company and per hectare is lower than the national average. About 80% of the work is carried out within the family. The succession percentage lags behind the national level, but there are relatively slightly more young entrepreneurs. There are many potential quitters over 55 years old in study area, who manage one eighth of the cultivated land. One in ten entrepreneurs has an organic business. Multifunctional agriculture continues to increase. The analysis was carried out using the CBS Agricultural Census.

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)0.003
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.361
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0030.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0570.001

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 head0.013
GPT teacher head0.237
Teacher spread0.225 · 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

Explore more

Same topicEnergy, Environment, Agriculture AnalysisFrench-language works237,207