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Record W4387194781 · doi:10.18174/632573

Regeneratieve landbouw : ervaringen en lessen uit een Community of Practice

2023· report· nl· W4387194781 on OpenAlexaff
A.B. Smit, Mark Manshanden, A.C.G. Beldman, Marjolijn de Boer

Bibliographic record

Venuenot available
Typereport
Languagenl
FieldEnvironmental Science
TopicEnvironmental Conservation and Management
Canadian institutionsImpact
Fundersnot available
KeywordsAgricultureSocioeconomic statusSustainabilityBusinessGeographySocioeconomicsSociologyDemographyArchaeologyEcology

Abstract

fetched live from OpenAlex

Regeneratieve Agriculture (RA) is a form of agriculture in which the farmer tries to positively score on all biophysical and socioeconomic aspects of sustainability. RA focuses on the outcomes, not on the measures taken. In the past four years, a Community of Practice of 18 farmers has been followed, who have been working towards RA for a shorter or longer period of time. Different farm and soil types and regions were involved as well as very different types of measures that had been taken to reach the outcomes desired. Their approach offers inspiration for other farmers that also want to move into the direction of RA, although monitoring their outcomes appeared a big challenge.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient 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 score0.160
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0110.006

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 head0.110
GPT teacher head0.339
Teacher spread0.229 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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