A new method for the measurement of meteorite bulk volume via ideal gas pycnometry
Bibliographic record
Abstract
To date, of the many techniques used to measure the bulk volume of meteorites, only three methods (Archimedean bead method, 3‐D laser imaging and X‐ray microtomography) can be considered as nondestructive or noncontaminating. The bead method can show large, random errors for sample sizes of smaller than 5 cm 3 . In contrast, 3‐D laser imaging is a high‐accuracy method even when measuring the bulk volumes of small meteorites. This method is both costly and time consuming, however, and meteorites of a certain shape may lead to some uncertainties in the analysis. The method of X‐ray microtomography suffers from the same problems as 3‐D laser imaging. This study outlines a new method of high‐accuracy, nondestructive and noncontaminating measurement of the bulk volume of meteorite samples. In order to measure the bulk volume of a meteorite, one must measure the total volume of the balloon vacuum packaged meteorite and the volume of balloon that had been used to enclose the meteorite using ideal gas pycnometry. The difference between the two determined volumes is the bulk volume of the meteorite. Through the measurement of zero porosity metal spheres and tempered glass fragments, our results indicate that for a sample which has a volume of between 0.5 and 2 cm 3 , the relative error of the measurement is less than ±0.6%. Furthermore, this error will be even smaller (less than ±0.1%) if the determined sample size is larger than 2 cm 3 . The precision of this method shows some volume dependence. For samples smaller than 1 cm 3 , the standard deviations are less than ±0.328%, and these values will fall to less than ±0.052% for samples larger than 2 cm 3 . The porosities of nine fragments of Jilin, GaoGuenie, Zaoyang and Zhaodong meteorites have been measured using our vacuum packaging–pycnometry method, with determined average porosities of Jilin, GaoGuenie, Zaoyang and Zhaodong of 9.0307%, 2.9277%, 17.5437% and 5.9748%, respectively. These values agree well with the porosities of fragments of which have been measured using the Archimedean bead method and 3‐D laser imaging. This method also may be applied to the study of rare samples in other fields (e.g., archeology and geology).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".