4STAR hyperspectral sunphotometry measurements during the Oil Sands 2018 campaign near Fort McMurray, Alberta
Bibliographic record
Abstract
In 2018, the Environment and Climate Change Canada (ECCC) in close collaboration with the National Research Council (NRC) planned and conducted an intensive airborne oil sands measurement campaign (OSMC) based out of Fort McMurray, Alberta. The campaign was conducted in two phases: Phase I (April 3-15) and Phase II (May 28-July 5). In preparation for the OSMC the NRC, together with NASA, have integrated a novel 4STAR sunphotometer on board the Convair-580 for the measurements of aerosols and trace gases. The 4STAR primary capability is to supply hyperspectral measurements of the aerosol optical depth (AOD) - the most important aerosol radiative parameter indicative of the total column vertical extinction due to aerosols. The main purposes of this report are to describe the performance of the 4STAR during the OSMC, discuss data availability statistics and provide a first look at some of the initial results.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".