Management Committee meeting 2020 Report, by the CA15212
Bibliographic record
Abstract
On the occasion of the Management Committee (MC) and Working Group Meeting of the COST Action 15212 Citizen Science to promote creativity, scientific literacy, and innovation throughout Europe, an overview of the outcomes, to reflect usability, to enhance update by the community and to discuss and initiate further steps was prepared. As the COST Action is coming to an end, the results of the work were presented by the leaders of the working groups. The claim to pass on the outputs and findings is secured by two future steps: Firstly, there will be a subsequent COST Action and secondly, the results can be made available to the public in summary form on the new transnational platform EU-Citizen.Science. This article/publication is based upon work from COST Action 15212, supported by COST (European Cooperation in Science and Technology). Due to the pandemic, the final conference was organised online for a few hours instead of several days with the technical support of Leiden University and the online service zoom.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.163 | 0.246 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".