Evaluation of a new JMA aircraft flask sampling system and laboratory trace gas analysis system
Bibliographic record
Abstract
Abstract. We established and evaluated a flask air sampling system on a cargo C-130H aircraft, as well as a trace gas measurement system for the flask samples, as part of a new operational monitoring program of the Japan Meteorological Agency (JMA). Air samples were collected during each flight, between Kanagawa Prefecture (near Tokyo) and Minamitorishima (an island located nearly 2000 km southeast of Tokyo), from the air-conditioning system on the aircraft. Prior to the operational employment of the sampling system, a quality assurance test of the sampled air was made by specially coordinated flights at a low altitude of 1000 ft over Minamitorishima and comparing the flask values with those obtained at the surface. Based on our storage tests, the flask samples remained nearly stable until analyses. The trace gas measurement system has, in addition to the nondispersive infrared (NDIR) and vacuum ultraviolet resonance fluorescence (VURF) analyzers, two laser-based analyzers using wavelength-scanned cavity ring-down spectroscopy (WS-CRDS) and off-axis integrated cavity output spectroscopy (ICOS). Laboratory tests of the laser-based analyzers for measuring flask samples indicated relatively high reproducibility with overall precisions of less than ±0.06 ppm for CO2, ±0.68 ppb for CH4, ±0.36 ppb for CO, and ±0.03 ppb for N2O. Flask air sample measurements, conducted concurrently on different analyzers were compared. These comparisons showed a negligible bias in the averaged measurements between the laser-based measurement techniques and the other methods currently in use. We also estimated that there are no significant isotope effects for CH4, CO and N2O using standard gases with industrial isotopic compositions to calibrate the laser-based analyzers, but CO2 was found to possess isotope effects larger than its analytical precision.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".