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Record W6911424435 · doi:10.5281/zenodo.11443006

Open Field Day events & associated Comms/Diss Reports - D8.7

2023· article· en· W6911424435 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsnot available
Fundersnot available
KeywordsTimelineOpenness to experienceField (mathematics)Quarter (Canadian coin)DisseminationDocumentationOpen scienceInformation Dissemination

Abstract

fetched live from OpenAlex

SustainSahel’s dissemination approach is now at its second year of implementation, and the open field days are one of its key elements. From the planning phase, the open field days created concrete synergies between the project partners, WPs and disciplines, thus kickstarting the transdisciplinary collaboration within the project frame on the ground and acting as a platform for mutual learning. Despite initial delays due to changes in the project’s consortium, the project partners took the dissemination approach in their hands and the first open field days were organized in six project sites in the second quarter of 2022. By now, 19 open field days have been organized in six project sites, to which 9 additional events by the project’s dissemination expansion sister project – DAAPS – can be added. The relatively early start of the dissemination approach in the timeline of the project is already yielding its fruits, with a consolidated collaboration between farmers, researchers, farmers’ organizations, students and extension officers that facilitates the flow of information and the openness to each other’s perspectives and messages. The open field days are integrated into a systemic approach, where links to the Innovation Platforms (IP) and to the newly created internal sharing forum contribute to deepening the discussions on the proposed CSL practices and the pathway to their adoption. SustainSahel partners had the opportunity to attend a four week comprehensive online training organized in 12 different modules, covering all aspects and steps regarding the farmer field school approach. This was a significant additional activity and external funding originally not foreseen in the DoA brought to the project. The current deliverable highlights the connections between the open field days and other elements of the project’s dissemination approach, providing insights into what has already been achieved, as well as an update on the latest decisions and the vision concerning the upcoming phases.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.136
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.005

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 head0.047
GPT teacher head0.250
Teacher spread0.203 · 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
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
Published2023
Admission routes1
Has abstractyes

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