Tunable All-Fiber Laser for Remote Sensing of Methane Near 3.4 μm
Bibliographic record
Abstract
The mid-infrared (MIR) region of the optical spectrum has drawn considerable scientific interest in the past few years. Indeed, several molecules relevant to medical or environmental conundrums exhibit strong absorption lines in this region: for instance, methane lines in the MIR are up to 100 times stronger than in the near-infrared [1]. In turn, fiber lasers have long stood as prime candidates for remote gas detection in outdoor environments, given their exemplary robustness, power scaling and beam quality. However, while several previous contributions have targeted methane bands under 3.3 μm in wavelength [2], little work has been done to push fiber laser detection tools past 3.4 μm, where methane absorption lines are mostly decoupled from the absorption spectra of water and other atmospheric constituents. This is especially relevant when probing CH4through a gas mixture with relatively high water content, such as when studying gas emission from methane-rich thermokarst lakes in northern regions.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".