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Record W2092752778 · doi:10.1088/0022-3727/35/21/305

Sensitivity reduction in biased amorphous selenium photoconductors

2002· article· en· W2092752778 on OpenAlexafffund
S Steciw, T. Stanescu, S Rathee, B. G. Fallone

Bibliographic record

VenueJournal of Physics D Applied Physics · 2002
Typearticle
Languageen
FieldMaterials Science
TopicLuminescence Properties of Advanced Materials
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSensitivity (control systems)Electric fieldIrradiationPhotonAmorphous solidOpticsPhysicsMaterials scienceAnalytical Chemistry (journal)Atomic physicsChemistryNuclear physics

Abstract

fetched live from OpenAlex

We have experimentally studied the reduction in x-ray sensitivity of individual biased amorphous selenium (a-Se) detectors as a function of radiation dose. This study was performed to understand the effects of detector parameters on the reduction of sensitivity in a-Se active matrix flat panel imagers, which results in latent `ghost' images. The sensitivity was measured for various x-ray dose rates, electric field strengths, and effective photon energies. The reduction of sensitivity has a weak dependence on the incident dose rate (reduces to 0.67 and 0.63 of original value after 100 cGy for dose rates of 2.73 cGy min−1 and 8.18 cGy min−1, respectively), is strongly affected by the applied electric field (reduces to 0.32 and 0.73 of original value after 100 cGy for electric fields of 0.6 V μm−1 and 5 V μm−1, respectively), and is greater for higher-energy photons. The measured sensitivity curves were fitted using a linear-exponential equation (reduced χ2 values averaging 0.73). Experiments demonstrated that a-Se recovers approximately 20% of its original sensitivity at 30 min post-irradiation. If a-Se is allowed to recover its sensitivity for 24 h between irradiation, the initial measured current is a linear function of both the dose rate and applied electric field.

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 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)0.001
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 score0.008
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.032
GPT teacher head0.238
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations17
Published2002
Admission routes2
Has abstractyes

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