Bibliographic record
Abstract
Denne guide henvender sig til indkøbere i den nordiske sundhedssektor, som er ansvarlige for indkøb af tekstilprodukter og -services, og bistår dem med at udvikle processer til at indføre passende og praktisk gennemførlige miljøkriterier i udbudsdokumenter. Indkøbere kan lære, hvilke aspekter af produktion og behandling af tekstiler der har den største betydning for miljøet, og hvordan disse kan behandles gennem kriterierne. De kan lære mere om miljømærkernes rolle i indkøbsprocessen og finde links til kriterier, der er klar til brug, og andre nyttige oplysninger fra nationale myndigheder. Guiden er udviklet i samarbejde med et nordisk netværk af indkøbere i sundhedssektoren som en del af et initiativ under den nordiske handlingsplan for bæredygtig mode og tekstil “Velklædt i et rent miljø”. Det er finansieret af No rdisk Ministerråd.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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; both teacher heads agree on what is shown here.
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".