Effect of laser wavelength on soil carbon measurements using laser-induced breakdown spectroscopy
Bibliographic record
Abstract
We investigate the effect of laser wavelength on laser-induced breakdown spectroscopy (LIBS) on the measurement of carbon in agricultural soils. Two laser wavelengths, 1064 nm and 532 nm, were used to determine soil carbon concentration. No chemical pretreatment, grinding, or pelletization was performed on soil samples to simulate in-field conditions. A multivariate calibration model with outlier filtering and optimized parameters in partial least squared regression (PLSR) was established and validated. The calibration model estimated carbon content in soils with an average prediction error of 4.7% at a laser wavelength of 1064 nm and 2.7% at 532 nm. The limit of detection (LOD) range for 532 nm was 0.34-0.5 w/w%, approximately half of the LOD range for 1064 nm laser wavelength. The improvement in prediction error and LOD of LIBS measurements is attributed to the increase in plasma density achieved at 532 nm.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".