Charge transport and trapping-limited sensitivity and resolution of pixellated x-ray image detectors
Bibliographic record
Abstract
Charge transport and trapping-limited sensitivity and signal spreading over neighboring pixels of a direct conversion pixellated x-ray image detector are calculated by using the final trapped charge distributions across the photoconductor and the weighting potential of the individual pixel. The analytical expressions for the final trapped charge distributions across the photoconductor are derived by analytically solving the continuity equation for both types of carriers (electrons and holes). We calculate collected charges at different pixels by considering square pixels arranged in a two dimensional array. We calculate the amount of collected charge per unit incident radiation, the <i>x-ray sensitivity</i>, in terms of normalized parameters; (a) the normalized absorption depth (= absorption depth/photoconductor thickness), (b) normalized electron schubweg (schubweg/thickness), (c) normalized hole schubweg, and (d) normalized pixel pitch (pixel size/thickness). The composite (finely sampled) line spread function (LSF) is calculated by calculating collected charges at different pixels and by considering diagnostic x-ray irradiation along a line. The modulation transfer function (MTF) due to distributed carrier trapping is calculated by taking Fourier transform of composite LSF and correcting for the square sampling aperture. The charge transport and trapping-limited sensitivity and resolution of pixellated x-ray detectors mostly depend on the mobility and lifetime product of charges that move towards the pixel electrodes and the extent of dependence increases with decreasing normalized pixel pitch. The polarity (negative or positive signal) and the quantity of induced signals in the surrounding pixels depend on the bias polarity and the rate of trapping of both types of carriers. Optimal sensitivity and resolution can be attained by ensuring that the carriers which drift towards the pixel electrodes have a schubweg much longer than the sample thickness.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".