Composition of the Chandra ACIS contaminant
Bibliographic record
Abstract
The Advanced CCD Imaging Spectrometer (ACIS) on the Chandra X-ray Observatory is suffering a gradual loss of low energy sensitivity due to a buildup of a contaminant. High resolution spectra of bright astrophysical sources using the Chandra Low Energy Transmission Grating Spectrometer (LETGS) have been analyzed in order to determine the nature of the contaminant by measuring the absorption edges. The dominant element in the contaminant is carbon. Edges due to oxygen and fluorine are also detectable. Excluding H, we find that C, O, and F comprise >80%, 7%, and 7% of the contaminant by number, respectively. Nitrogen is less than 3% of the contaminant. We will assess various candidates for the contaminating material and investigate the growth of the layer with time. For example, the detailed structure of the C-K absorption edge provides information about the bonding structure of the compound, eliminating aromatic hydrocarbons as the contaminating material.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".