Perceptions of scale in hydrology: what do you mean by regional scale?
Bibliographic record
Abstract
The discipline of hydrology has a long history of research in the practical and theoretical aspects of scaling and scale issues, but little effort has been focused on hydrologists’ perception of the scale terms. What exactly do hydrologists mean when they use the terms “pore scale” or “regional scale”? The application of hydrological research requires clear communication, both within the discipline, and with a broader audience. Quantitative and qualitative data on hydrologists’ perceptions of scale were collected using voluntary written surveys and face-to-face interviews. The results suggest that most hydrologists do not consistently define scale terms in the literature, and that this is a minor impediment when interacting with other disciplines and stakeholders. Yet, surface water and groundwater hydrologists agree, within one to two orders of magnitude, on the length scale for most scale terms. Most respondents suggest that the hydrological community needs to better define the length scale of scale terms. In the short term, hydrologists could more frequently and consistently clarify their own length scales whenever a scale term is used. A common and consistent language of scale for hydrological researchers could better enable communication, research, teaching and outreach. Editor Z.W. Kundzewicz; Associate editor T. WagenerCitation Gleeson, T. and Paszkowski, D., 2013. Perceptions of scale in hydrology: what do you mean by regional scale? Hydrological Sciences Journal, 59 (1), 99–107.
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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 | 0.022 | 0.060 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.018 |
| Scholarly communication | 0.007 | 0.017 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".