A silicon sensor study for the ILD ECAL
Bibliographic record
Abstract
The International Large Detector (ILD) is a proposed detector for the International Linear Collider (ILC). It has been designed to achieve an excellent jet energy resolution by using Particle Flow Algorithm (PFA), which relies on the ability to separate nearby particles within a jet. PFA requires the calorimeters with high granularity. A sampling calorimeter with tungsten plates and silicon sensors is proposed for the Electromagnetic Calorimeter (ECAL). Thirty layers of tungsten plates, with total thickness of about 24 X0, are chosen for small Moliere radius to minimize overlap of electromagnetic showers. Fine granularity is achieved by using silicon sensors having 256 pixels of 5.5×5.5 mm 2 in an area of 9×9 cm 2 . The total number of readout channels amounts to the order of 10 8 . We have measured various properties of these prototype sensors: the leakage current, capacitance, and full depletion voltage. To optimize the sensor design, we have also examined relation of the guard ring structure and the cross talk between pixels using an infrared laser system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 |
| 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".