Determination of bulk density for small meteorite fragments via visible light 3‐D laser imaging
Bibliographic record
Abstract
Abstract– Bulk density is an important intrinsic property of meteorites, but the necessary bulk volume measurement is difficult to do in a truly nondestructive way. Archimedean methods involving the displacement of a 40–100 μm beads “fluid” are commonly applied, but can encounter systematic errors. Herein, we report a visible light laser imaging technique for the nondestructive measurement of meteorite surface features, allowing for the subsequent assembly of 3‐D volumetric models; the method is particularly applicable to small meteorite fragments and to fragile specimens. We have acquired laser image data for 24 fragments from 18 ordinary chondrites, carbonaceous chondrites, and achondrites, with masses ranging from 265.0 to 1.2 g. Laser imaging bulk density is consistent between sister fragments of meteorites down to sizes of about 0.5 cm3, an order of magnitude smaller than can be reliably measured with Archimedean beads techniques. Uncertainty is less than 2% for fragments >4 cm3, and typically between 2 and 4% for small fragments <4 cm3. For 10 fragments, 3‐D laser imaging volumes are on average 1.3% smaller than those obtained with Archimedean beads. In a wider comparison using 21 meteorite fragments, 3‐D laser imaging bulk densities are on average 2.14 ± 2.36% greater than the corresponding Archimedean method literature values for these meteorites. Difficulties in the procedure of 3‐D image alignment may lead to a slight overestimation of meteorite bulk density, and so laser imaging‐based bulk densities are maximum estimates that can be viewed as being complementary to the minimum bulk density estimates obtained using Archimedean beads methods.
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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 | 0.000 | 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".