A study of the material in the ATLAS inner detector using secondary hadronic interactions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The ATLAS inner detector is used to reconstruct secondary vertices due to hadronic \ninteractions of primary collision products, so probing the location and amount of material in the \ninner region of ATLAS. Data collected in 7 TeV pp collisions at the LHC, with a minimum bias \ntrigger, are used for comparisons with simulated events. The reconstructed secondary vertices \nhave spatial resolutions ranging from 200 mm to 1 mm. The overall material description in the \nsimulation is validated to within an experimental uncertainty of about 7%. This will lead to a better \nunderstanding of the reconstruction of various objects such as tracks, leptons, jets, and missing \ntransverse momentum.
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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 it