Bibliographic record
Abstract
3D laser imaging is a non-destructive method devised to calculate bulk density by creating volumetrically accurate computer models of hand samples.The focus of this research was to streamline the imaging process and to mitigate any potential errors.3D laser imaging captured with great detail (30 voxel/mm 2 ) surficial features of the samples, such as regmaglypts, pits and cut faces.Densities from 41 iron meteorites and 9 splash-form Australasian tektites are reported here.The laser-derived densities of iron meteorites range from 6.98 to 7.93 g/cm 3 .Several suites of meteorites were studied and are somewhat heterogeneous based on an average 2.7% variation in inter-fragment density.Density decreases with terrestrial age due to weathering.The tektites have an average laser-derived density of 2.41+0.11g/cm 3 .For comparison purposes, the Archimedean bead method was also used to determine density.This method was more effective for tektites than for iron meteorites.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".