Spatial Patterns of Urban Dew and Surface Moisture in Vancouver, Canada, During Summer
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
Boundary layer climatology is often concerned with processes on an idealised extensive, homogeneous plain, where a single point sample suffices to characterise surface conditions. Such landscapes are rare but a large, flat field or pasture can be a reasonable approximation. In a patchy landscape, surface characteristics vary spatially and a single point measurement is inadequate. Dew is seldom measured in cities but its accumulation is expected to vary spatially in interesting ways because the city surface is a complicated mosaic of different materials. This study presents the results of a hardware modelling project to study dew (condensation) and surface water (dew + guttation) in an urban residential neighbourhood. A 1/8th scale, out-of-doors model with a simplified geometry was constructed and run in Vancouver, BC, Canada, during summer. The Internal Thermal Mass (ITM) approach to scaling was used to modify the thermal inertia of the model buildings so that nocturnal surface temperatures would be duplicated in real time. It was postulated that dew accumulation (mm d-1) would be also duplicated. Dew, surface temperature and sky view factor in the model varied in explainable patterns, i.e. grass was cooler and wetter at open sites with large sky view, and was warmer and accumulated less dew close to buildings and under trees, where sky view was reduced. This strong association suggests that maps of site geometry expressed as sky view factor could potentially be used to create maps of dew in cities and other patchy landscapes.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it