Compositional tomography of a gold‐bearing sample by Laser‐induced breakdown spectroscopy
Bibliographic record
Abstract
Abstract This contribution presents the first results of compositional tomography of a geological sample. The volume render of 6 × 8 × 1 mm3 was constructed by assembling 63 compositional maps acquired in 21 min (19.5 s/layer) by laser‐induced breakdown spectroscopy (LIBS), which determines the chemical composition of the analysed spot from the light emitted by a plasma produced by the laser. This technique is, therefore, able to directly reveal the 3D distribution of chemical elements in a sample. As an example, the spatial distribution and 3D geometry of visible gold in an ultramafic schist are presented. Inasmuch as this newly developed portable LIBS instrument is able to the rapidly characterize the 3D geometry of any geological materials, it has a high potential to be useful for the mining industry and for a wide range of geosciences, such as structural geology, petrology, sedimentology and economic geology.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".