More on the Possible Composition of the Meridiani Hematite-Rich Concretions
Bibliographic record
Abstract
Elsewhere in these proceedings, Schneider et al. discuss compositional constraints on hematite-rich spherule (blueberry) formation at Meridiani Planum. Schneider et al. provide the background for work done to date to understand the composition and mineralogy of the spherules and devise a test of possible concretion growth processes. They also report the results of area analyses of spherules in targets analyzed with the Alpha Particle X-ray Spectrometer (APXS) and test several possible models for included components other than hematite. In this abstract, we use the compositional trends for spherule-rich targets to compute possible elemental compositions of the spherules. This approach differs from that of, which also used a determination of the area of spherules in APXS targets, coupled with a correction for the radial acceptance function, to try to un-mix the compositions directly, using 2 and 3-component models and mass balance. That approach contained a fair amount of uncertainty owing to problems associated with irregular and heterogeneous target geometry, unknown composition of non-spherule lithic components, and variable dust coatings on spherules. Since then, Opportunity has analyzed additional spherule-rich targets, and the compositional trends so obtained permit a more direct assessment of the data.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".