Consistent characterisation factors at midpoint and endpoint relevant to agricultural water scarcity arising from freshwater consumption
Bibliographic record
Abstract
The shortage of agricultural water from freshwater sources is a growing concern because of the relatively large amounts needed to sustain food production for an increasing population. In this context, an impact assessment methodology is indispensable for the identification and assessment of the potential consequences of freshwater consumption in relation to agricultural water scarcity. This paper reports on the consistent development of midpoint and endpoint characterisation factors (CFs) for assessing these impacts. Midpoint characterisation factors focus specifically on shortages in food production resulting from agricultural water scarcity. These were calculated by incorporating country-specific compensation factors for physical availability of water resources and socio-economic capacity in relation to the irrigation water demand for agriculture. At the endpoint, to reflect the more complex impact pathways from food production losses to malnutrition damage from agricultural water scarcity, international food trade relationships and economic adaptation capacity were integrated in the modelling with measures of nutritional vulnerability for each country. The inter-country variances of CFs at the midpoint revealed by this study were larger than those derived using previously developed methods, which did not integrate compensation processes by food stocks. At the endpoint level, both national and trade-induced damage through international trade were quantified and visualised. Distribution of malnutrition damage was also determined by production and trade balances for commodity groups in water-consuming countries, as well as dependency on import ratios for importer countries and economic adaptation capacity in each country. By incorporating the complex relationships between these factors, estimated malnutrition damage due to freshwater consumption at the country scale showed good correlation with total reported nutritional deficiency damage. The model allows the establishment of consistent CFs at the midpoint and endpoint for agricultural water scarcity resulting from freshwater consumption. The complex relationships between food production supply and nutrition damage can be described by considering the physical and socio-economic parameters used in this study. Developed CFs contribute to a better assessment of the potential impacts associated with freshwater consumption in global supply chains and to life cycle assessment and water footprint assessments.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".