Building consensus on a generic water scarcity indicator for LCA-based water footprint: preliminary results from WULCA
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Consuming water can affect human health (e.g. by reducing availability of irrigation water and hence food availability), ecosystems (by decreasing water availability for terrestrial/aquatic species) and future generations (by depleting non-renewable resources). However, no standard method exists to quantify the stress on water without favoring any of these areas of protection. Stress/scarcity indexes have fo-cused on an anthropocentric perspective, and a few on an ecocentric perspective. We explore the possibility of developing an indicator considering the water resource as a whole and propose a method which is not centered on an area of protection but rather assesses the ex-tent to which all water demand and availability differ within a watershed (i.e. hydrocentric). This concept can eventually serve as a single metric to assess potential impacts from water use and be used consistently in the application of the upcoming ISO standard and for ecolabelling of food and energy products.
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.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it