DiSSCo Prepare Milestone report MS8.4 - Procurement Strategy and Policy
Bibliographic record
Abstract
The Distributed System of Scientific Collections Research Infrastructure (DiSSCo-RI) will need to build strategic partnerships with industrial stakeholders, and a procurement framework will be required in order to maximise these opportunities. This document (DiSSCo Prepare Milestone 8.4) looks at procurement from three perspectives: 1) strategic partnerships and co-creation; 2) the procurement legal framework; and, 3) green procurement policy. It highlights best practices in procurement, and where possible it considers how procurement frameworks have been implemented in other relevant European Research Infrastructures (RIs). Many of the areas described will help to inform DiSSCo Prepare WP4 and WP7, and it will be used as a basis for the stakeholder analysis and engagement activities of DiSSCo Prepare Task 8.3.
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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 | 0.020 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.009 | 0.005 |
| Insufficient payload (model declined to judge) | 0.098 | 0.079 |
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".