Sensitivity reduction in biased amorphous selenium photoconductors
Bibliographic record
Abstract
We have experimentally studied the reduction in x-ray sensitivity of individual biased amorphous selenium (a-Se) detectors as a function of radiation dose. This study was performed to understand the effects of detector parameters on the reduction of sensitivity in a-Se active matrix flat panel imagers, which results in latent `ghost' images. The sensitivity was measured for various x-ray dose rates, electric field strengths, and effective photon energies. The reduction of sensitivity has a weak dependence on the incident dose rate (reduces to 0.67 and 0.63 of original value after 100 cGy for dose rates of 2.73 cGy min −1 and 8.18 cGy min −1 , respectively), is strongly affected by the applied electric field (reduces to 0.32 and 0.73 of original value after 100 cGy for electric fields of 0.6 V μm −1 and 5 V μm −1 , respectively), and is greater for higher-energy photons. The measured sensitivity curves were fitted using a linear-exponential equation (reduced χ 2 values averaging 0.73). Experiments demonstrated that a-Se recovers approximately 20% of its original sensitivity at 30 min post-irradiation. If a-Se is allowed to recover its sensitivity for 24 h between irradiation, the initial measured current is a linear function of both the dose rate and applied electric field.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".