Hunting for Hydrated Minerals on Trans-Neptunian Objects
Bibliographic record
Abstract
Abstract We present new optical reflectance spectra of three potentially silicate-rich trans-Neptunian objects (TNOs). These spectra were obtained with the aim of confirming past hints and detections of λ ∼ 0.7 μm absorption features associated with the presence of iron-bearing phyllosilicates. Our new spectrum of 120216 (2004 EW95) presents clearly detected absorption features that are similar in shape to hydrated mineral absorption bands present in the spectra of aqueously altered outer main belt asteroids. Four new reflectance spectra of 208996 (2003 AZ84) obtained at separate epochs all appear featureless, but they vary significantly in spectral gradient (between ∼3.5%/0.1 μm and ∼8.5%/0.1 μm) on a timescale consistent with this object’s nominal rotational period. We report the first four optical reflectance spectra of 90568 (2004 GV9), finding them all to be featureless but consistent with colors previously reported for this object. We speculate that impacts are the only mechanism capable of delivering, excavating, or forming hydrated minerals at the surfaces of TNOs in detectable concentrations; as a result, any deposits of hydrated minerals on TNOs are predicted to be localized and associated with impact sites. Globally altered TNOs (as observationally suggested for 2004 EW95) plausibly formed more easily at smaller heliocentric distances (r H < 15 au) before being transplanted into the current trans-Neptunian population.
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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 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".