Exploring the ability of current climate information to facilitate local climate services for the water sector
Bibliographic record
Abstract
Local climate services become increasingly necessary in making adaptation to our changing climate more understandable and manageable. The ability of current climate information to develop and support local climate services for water resources management in close collaboration with local users of the water sector from the island of Crete is being explored. Climate modeling output ranging from event scale to decadal and centennial experiments, at hourly to monthly temporal scales and at high resolution (2 Km) to GCM spatial scales (100–250 km), are used to assess climate change impacts on water resources availability and extremes. A robust signal of temperature increase and precipitation decrease is projected for all future periods, in parallel to an increase in magnitude of extreme precipitation. Several messages could be extracted from the provider – user interaction such as the communication of basic concepts and uncertainties, user skepticism and feedback. The frequent personal contact, the communication in layman’s terms of the limitations of the climate impact modeling and the corresponding uncertainties, is the key to successful provisions of suitable information.
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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 | 0.014 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 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; 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".