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Record W2903333303 · doi:10.1088/1361-6463/aaf556

Cadmium zinc telluride pixel detectors for high-intensity x-ray imaging at free electron lasers

2018· article· en· W2903333303 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Physics D Applied Physics · 2018
Typearticle
Languageen
FieldEngineering
TopicAdvanced Semiconductor Detectors and Materials
Canadian institutionsRedlen Technologies (Canada)
FundersScience and Technology Facilities Council
KeywordsCadmium zinc tellurideCadmiumCadmium telluride photovoltaicsZincLaserOptoelectronicsIntensity (physics)ElectronOpticsMaterials scienceDetectorPhysicsNuclear physicsMetallurgy

Abstract

fetched live from OpenAlex

Abstract This paper reports the first demonstration of high-intensity x-ray imaging using cadmium zinc telluride (CdZnTe) pixel detectors at a free electron laser (FEL). Prototype detectors were produced using the STFC large pixel detector (LPD) ASIC and sensors fabricated from a novel high-intensity-capable CdZnTe material produced by Redlen Technologies. Characterisation of the performance of this sensor material was completed at the Linac Coherent Light Source (LCLS) FEL. The detectors were operated at a frame rate of 1 MHz with 9.5 keV x-ray pulses delivered at a rate of 120 Hz. Measurements successfully demonstrated the linear response of the CdZnTe material to increasing numbers of x-rays up to a fluence of 8 GeV mm −2 per pulse, the limit of the dynamic range of the LPD ASIC.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.008
GPT teacher head0.214
Teacher spread0.206 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it