A fundamental parameters approach to calibration of the Mars Exploration Rover Alpha Particle X‐ray Spectrometer: 2. Analysis of unknown samples
Bibliographic record
Abstract
Our fundamental parameters method was recently applied to results from geochemical reference materials to provide a new calibration of the laboratory Alpha Particle X‐ray Spectrometer (APXS) instrument from the Mars Exploration Rovers mission. The method is now extended to provide an iterative approach for the treatment of unknown samples, based upon that initial calibration. It is tested by regarding small subsets of the reference materials and other materials as unknown samples; agreement of derived element concentrations with suppliers' recommended values is good with the exception of certain igneous rock types. In these exceptions, the deviations can be explained via the location of the elements concerned in minority or accessory mineral phases, and different calibration schemes can be developed empirically for specific rock types which are defined via a TAS diagram. The necessary reliance upon an iterative approach in normalizing the sum of oxide concentrations to 100% is investigated. It turns out that this can cause significant errors in derived element concentrations when a significant amount of mineralogically bound water (H2O+) is present, but our method has been extended to enable determination of this H2O+ concentration under known geometry. Various implications for calibration of the new APXS selected for the Mars Science Laboratory are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".