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Record W7130315913 · doi:10.5281/zenodo.18683289

D6.3 Economic Assessment of Soil Biodiversity Enhancement at Farm, Regional and EU Level

2025· article· W7130315913 on OpenAlexaff
Martin Banse, Omid Zamani, Christine van Capelle, Javier Calatrava, David Martínez-Granados, Irene Ollio, Miguel Rodriguez Mendez, Marina Gómez, Anne Põder, O. V. Aleksandrova, jo bijttebier, Hilde Wustenberghs, David-Alexander Bind, Birte Tschentke, Timo Karhula, Miettinen,, Antti, Eija Pouta

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typearticle
Language
FieldEnvironmental Science
TopicSustainable Agricultural Systems Analysis
Canadian institutionsInnovation Cluster (Canada)
FundersEuropean Commission
KeywordsDeliverableEuropean commissionBiodiversityEuropean unionWork (physics)AgricultureEconomic impact analysisImpact assessmentCommission

Abstract

fetched live from OpenAlex

This deliverable 6.3 of the SoildiverAgro project analyses the economic and environmental implications of enhancingsoil biodiversity in European agriculture to promote stability, resilience, and reduced dependency on external inputs.This report assesses the financial viability of biodiversity-friendly farming practices at farm, regional, and EU levels. This work was funded by the European Commission Horizon 2020 project SoildiverAgro [grant agreement 817819].

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)0.003
metaresearch head score (Gemma)0.003
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: Other
Teacher disagreement score0.018
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0180.004

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 head0.029
GPT teacher head0.239
Teacher spread0.210 · 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
Published2025
Admission routes1
Has abstractyes

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