De toekomst van het stedelijk watersysteem: opereren in een stad vol transities
Bibliographic record
Abstract
Gedreven door ontwikkelingen zoals klimaatverandering, verstedelijking en digitalisering zien we in het stedelijk watersysteem steeds vaker oplossingen ‘buiten de buis’. Oplossingen zoals publieke pleinen met een waterbergende functie, polderdaken met een dynamische waterberging, zwembaden verwarmd met warmte uit (afval)water; het zijn allemaal pogingen om antwoorden te vinden op de uitdagingen waar de watersector mee te maken heeft. Echter, de watersector is niet de enige in de stad die worstelt met uitdagingen die dergelijke ontwikkelingen met zich meebrengen. Doordat de ruimte in de stad beperkt is, zien we dat de grenzen van stedelijke infrastructuur steeds vaker worden opgezocht, opgerekt en verlegd, om zo oplossingen te kunnen vinden die in te passen zijn in bestaand stedelijk gebied.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.045 | 0.006 |
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".