Water’s role in a circular food system
Bibliographic record
Abstract
Water is one of our greatest but finite resources and as such should be treated with special care. The framework for Community action in the field of water policy by the European Commission (Directive 2000/60/EC) states that water should be treated as heritage which needs to be protected. Water can vary in salinity, nutrient levels and levels of contamination (microbiological and/or chemical). For food production as well as for nature conservation, water plays a crucial role. In order to protect our fresh water sources from depletion, we need to reduce, reuse and recycle water in the most efficient way. Safeguard the future of our food supply and to prevent water from running out, the role of water in a circular food system needs to be made transparent. This report is innovative as it aims to open the dialogue about water’s role in a circular food system. Which types of waters could be identified from a circular perspective and to what extend do these interact with each other? The subdivision into green, blue and grey found in literature is enlightening, but falls short of giving a complete circular perspective. These three colours of water often represent a footprint approach related to one product (e.g. to produce one kilogram coffee requires x litres of fresh water). In this report a first exploration towards circular use is made to include nature in the analysis in addition to food production analysis. In order to broaden the dialogue of the representation of the world’s potential circular use of water, we have added six colours.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.044 |
| Scholarly communication | 0.009 | 0.015 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".