In situ evaluation of spaceborne CALIOP lidar measurements of the upper-ocean particle backscattering coefficient
Bibliographic record
Abstract
The spaceborne CALIOP lidar, initially designed for atmospheric measurements, was recently used to retrieve the particulate backscattering coefficient ( b bp ) in ocean subsurface layers. However, extensive field evaluation of CALIOP estimates was never conducted due to the scarcity of in situ data. Here, year-round and basin-wide data from Biogeochemical Argo floats (BGC Argo) were used to evaluate CALIOP estimates in the North Atlantic. The high density of BGC Argo float profiles in this region allowed us to test different matchup strategies at different spatio-temporal scales. When averaged over 2° by 2° grid boxes and monthly time resolution, CALIOP data present reasonably good correlation with highly variable float b bp values (correlation r = 0.44, root mean square relative error RMS % = 13.2%), suggesting that seasonal dynamics can be characterized at basin scale.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".