Highly validated atmospheric water vapor vertical profiles using Raman lidar technique
Bibliographic record
Abstract
Generating highly validated and well-resolved vertical profiles of water vapor is crucially important to understand short and long term global climate changes. Latest results of a newly developed water vapor Raman lidar instrument at the Environment Canada’s Centre for Atmospheric Research Experiments (CARE) (44°14'02" North, 79°45'40" West) will be presented. The CARE Raman lidar setup utilizes third harmonic (355 nm) output of employed YAG laser to probe aerosols, water vapor, and nitrogen profiles. By manipulating inelastic backscattering lidar signals of the Raman nitrogen channel (386.7 nm) and Raman water vapor channel (407.5 nm), vertical profiles of water vapor mixing ratio (WVMR) from the near ground up to 9 km geometrical altitude are routinely deduced, calibrated, validated, and compared against WVMR profiles obtained from simultaneously performed and collocated radiosonde launches. Seasonal effects and variations of WVMR will be also discussed and related to Raman lidar setup efficiency.
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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 | 0.000 | 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 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".