Understanding the advantage of remote femtosecond laser-induced breakdown spectroscopy of metallic targets
Bibliographic record
Abstract
We analyze the advantages of remotely sensing metallic targets using femtosecond laser-induced breakdown spectroscopy by studying the temperature and electron density of the plasma ejected from a lead target produced by femtosecond laser pulse filamentation in ambient air. The electron density of 8×1017cm−3 and the plasma temperature of 6794K were obtained for a 20ns time delay with respect to the laser pulse arriving on the target. With these values the signal is high, while the continuum blackbody radiation is low. The continuum emission in the fluorescence spectra is mainly associated with the supercontinuum of the distorted pulse during filamentation (white light laser) in air and this can be controlled. Extrapolation of the single-shot detection limit shows that this technique of filament-induced breakdown spectroscopy could be extended up to the kilometer range, opening up potential applications in metallurgic industry for remote material analysis and process controls.
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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) | 0.001 | 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".