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Record W4306644965 · doi:10.1002/aelm.202200640

Halide Perovskites for Direct Conversion Megavoltage X‐Ray Detectors

2022· article· en· W4306644965 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAdvanced Electronic Materials · 2022
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaProvincial Health Services Authority
KeywordsScintillatorDetectorMaterials scienceX-ray detectorHalideOptoelectronicsX-rayGadoliniumEnergy conversion efficiencySensitivity (control systems)OpticsPhotonPhysicsChemistryElectronic engineering

Abstract

fetched live from OpenAlex

Abstract Megavoltage (MV) X‐ray detectors used in cancer treatment either suffer from low sensitivity (scintillators) or prohibitively high cost (direct conversion). Here solution‐processed direct‐conversion MV X‐ray detectors are demonstrated based on halide perovskites. The authors’ prototype devices show a sensitivity of ≈0.7 µC Gy air −1 cm –2 , high photon‐to‐carrier conversion efficiency of 42 500%, and a signal‐to‐noise ratio of ≈1750 to 6 MV X‐ray beam of a medical linear accelerator. The detector shows a contrast of over −1.5% per cm of solid water, comparable to state‐of‐art commercial gadolinium oxysulfide (GOS) MV X‐ray scintillators. This work demonstrates the first prototype of low‐cost and efficient direct‐conversion MV X‐ray detectors.

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 categoriesInsufficient payload (model declined to judge)
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 score0.254
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.004
GPT teacher head0.201
Teacher spread0.197 · 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