The Fog Remote Sensing and Modeling (FRAM) field project and preliminary results
Bibliographic record
Abstract
The main purpose of this work is to describe a major field project on fog and summarize the preliminary results. The three field phases of Fog Remote Sensing and Modeling (FRAM) project were conducted over two regions of Canada: 1) Center for Atmospheric Research Experiments (CARE), Toronto, Ontario (FRAM-C), and 2) Lunenburg, Nova Scotia (FRAM-L1;L2). The FRAM-C component representing continental fog, and FRAM-L, representing the marine fog environment, took place from November 2005 to April 2006, and during June of 2006 and 2007, respectively. The main objectives of the project were 1) better description of fog environments, 2) development of microphysical parameterizations for model applications, 3) development of remote sensing methods for fog nowcasting/forecasting, 4) understanding of issues related to instrument capabilities and improvement of the analysis, and 5) integration of model data with observations to predict and detect fog areas and particle phase. During the project phases, various measurements at the surface, including droplet spectra and concentration, aerosol concentrations, visibility, 3D turbulent wind components, radiative fluxes, precipitation
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| 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".