Elemental analysis of sage (herb) using calibration-free laser-induced breakdown spectroscopy
Bibliographic record
Abstract
In this work, laser-induced breakdown spectroscopy (LIBS) has been used for the quantitative and qualitative analysis of the sage sample using the calibration-free LIBS (CF-LIBS) technique. The sage plasma is generated by focusing the second harmonics (532 nm) of a Q -switched Nd:YAG laser with a repetition rate of 10 Hz and pulse duration of 5 ns. The emission spectra are recorded using a LIBS 2000 detection system spectrometer consisting of five high-resolution spectrometers covering a wavelength range from 200 to 720 nm. The optical emission spectra of the sage sample reveal the spectral lines of Fe, Ca, Ti, Co, Mn, Ni, and Cr. The plasma temperature and electron number density of the neutral spectral lines of the pertinent elements have been deduced using the Boltzmann plot and Stark-broadening line profile method, with average values 8855 ± 885 K and 3.89 × 10 16 c m − 3 , respectively. The average values of the plasma parameters were used for the quantification of the detected elements in the sample. Based on the calibration-free method, the measured results demonstrate that Fe is the major constituent in the sample, having a percentage concentration of 48.1%, while the remaining elements are Ca, Ti, Co, Mn, Ni, and Cr, with percentage concentrations 0.7%, 5.3%, 8%, 11%, 12.3%, and 14.6%, respectively. This study demonstrates the feasibility of LIBS for the compositional analysis of major and trace elements present in the plant samples and its further applications in medicine.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".