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Record W3095819023 · doi:10.1016/j.mex.2020.101125

Method for the differentiation of radiation-induced photocurrent from total measured current in P3HT/PCBM BHJ photodiodes

2020· article· en· W3095819023 on OpenAlexafffund
Michael A. Hupman, Irina Valitova, Ian G. Hill, Alasdair Syme

Bibliographic record

VenueMethodsX · 2020
Typearticle
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsNova Scotia Health AuthorityDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhotocurrentPhotodiodeOptoelectronicsRadiationMaterials scienceCurrent (fluid)ChemistryOpticsPhysicsEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

Thin film radiation-detecting diodes fabricated in the laboratory, such as an organic bulk heterojunction, often contain conductive leads, indium tin oxide traces and metallic interconnects which are exposed to the high-energy photon beam during operation. These components generate extraneous radiation-induced currents, that, if not accounted for, will erroneously be attributed to the detector. In commercial devices, these contributions are mitigated by minimizing the size of these components, an approach that is often not feasible in a research lab. Here we demonstrate a method to measure these extraneous signals, and by subtraction, correct the gross signal to accurately reflect the signal generated in the active volume of the diode itself. The method can effectively correct the extraneous signal. The method showed promise over a range of photon beam energies, dose rates, and field sizes.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.002

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 head0.043
GPT teacher head0.304
Teacher spread0.261 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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

Citations4
Published2020
Admission routes2
Has abstractyes

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