Bibliographic record
Abstract
A physically based evapotranspiration model has been developed and tested in an experimental greenhouse. Good agreement was found between hourly model estimates and mass balance measurements of the latent heat flux. The model recognizes the advective nature of the greenhouse microclimate and thus represents an improvement over empirical model estimates of evaporation based on the measurement of radiation alone. Although radiant heating is the dominant mechanism responsible for evapotranspiration it does not represent a constant proportion on an hourly or daily basis. As a result, the Bowen ratio varies over time. Most of the variation was attributable to advection, and to a lesser extent, the sensible and latent heat fluxes at the glazing. During the daytime, the evapotranspiration process utilized in excess of 70% of the net available energy at the surface. However, model estimates and empirical evidence indicate this proportion can equal or exceed 100%. Variations in the latent heat flux are shown to depend on greenhouse design and the ambient microclimate. Simulation of the greenhouse humidity environment using 10 year hourly climatic means for Woodbridge, Ontario demonstrates the effect of modifying ventilation rates, glazing transmission and intake humidity on potential evapotranspiration. A relation is presented which permits the real-time adjustment of ventilation resistance from meteorological measurements of solar radiation and dry and wet-bulb air temperature. The maintenance of potential evapotranspiration for optimal crop productivity is shown to be incompatible with the collection and storage of sensible heat of the exhaust air as a means of defraying greenhouse heating costs.
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.
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 | 0.000 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".