OCO-3 Snapshot Area Mapping Mode: Early Results
Bibliographic record
Abstract
The NASA Orbiting Carbon Observatory-3 (OCO-3) was launched on May 4, 2019 to the International Space Station and has been taking measurements since August. OCO-3, like its predecessor OCO-2, makes hyperspectral measurements of reflected sunlight in three near-infrared bands. However, one of the unique features of OCO-3 is its ability to scan large contiguous areas on the order of 80 km by 80 km using a pointing mirror assembly. This capability, known as snapshot area mapping (SAM) mode, is being used to look at cities, forests, volcanos, and multiple other areas that are of interest to the carbon dioxide (CO2) and solar-induced chlorophyll fluorescence (SIF) scientific communities. For example, OCO-3 can measure column-mean CO2 (XCO2) over the entire Los Angeles, CA basin during the span of only two minutes. With several hundred SAMs having been collected so far and upwards of 25 possible per day, there is a wealth of data to investigate for scientific features and for any potential instrument biases. Additionally, this type of dense sampling will be a proof-of-concept for multiple future wide-swath CO2 missions. Here, we present several OCO-3 SAM mode measurements and discuss interesting features, XCO2 results, and future mission plans.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.007 |
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".