Multi-octave mid-infrared supercontinuum generation in a small-core step-index chalcogenide fiber
Bibliographic record
Abstract
Recently mid-infrared (MIR) supercontinuum (SC) generation has increasingly become a hot research topic as MIR SC sources should provide both broad bandwidth and high brightness, which is essential for applications such as micro-spectroscopy. Ideally for this application, the source should cover most of the characteristic absorption bands used to distinguish different biological materials and this means that the range from at least 2.5 µm to around 10 µm (1000 cm−1 to 4000 cm−1) is necessary with high average power. In this abstract, we report the generation of MIR SC spanning from 1.5 µm to 10 µm in a robust small-core step-index chalcogenide fiber at a peak pump power of ~3768 W, which to our knowledge, is the furthest spectrum into the MIR generated in chalcogenides with a relatively low peak pump power.
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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".