Airborne and Scanning LIDAR Results Obtained during the Pacific 2001 Air Quality Field Study
Bibliographic record
Abstract
Two different lidar platforms were employed in the Pacific 2001 Air Quality Field Study. A simultaneous upward/downward airborne lidar system called AERIAL (AERosol Imaging Airborne Lidar) was flown aboard the National Research Council of Canada, Convair 580 (CV580). The primary task of this platform was to establish a regional picture of particulate matter (PM) concentrations in the Lower Fraser Valley (LFV) of British Columbia. The high temporal and spatial resolution of the lidar provided images of PM stratification and boundary layer structure along predetermined flight lines. The flight lines were divided into a series of north-south and eastwest lines to provide a snapshot of the LFV as well as provide aerial support for four ground sites. There were 9 flights flown between 14 August and 30 August, including 2 night flights. The primary purpose of the night flights was to map PM transport in the lake valleys along the north range of the LFV. A scanning lidar facility called RASCAL (Rapid Acquisition SCanning Aerosol Lidar) was part of a suite of instruments making longer term measurements at the Langley Lochiel ground site. The lidar system was programmed to take three elevation scans (west, north and east) of the troposphere from the horizon to near zenith. Measurements were conducting for approximately 16 hours per day except longer during aircraft night flights. Results from both the airborne and scanning lidar facilities will be presented.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".