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Record W2161346183 · doi:10.1109/tnb.2008.2011851

Bioelectronic Imaging Array Based on Bacteriorhodopsin Film

2008· article· en· W2161346183 on OpenAlexafffund
Wei Wei Wang, George K. Knopf, Amarjeet Bassi

Bibliographic record

VenueIEEE Transactions on NanoBioscience · 2008
Typearticle
Languageen
FieldNeuroscience
TopicPhotoreceptor and optogenetics research
Canadian institutionsUniversity of WaterlooWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceResponsivityOptoelectronicsBacteriorhodopsinIndium tin oxideSIGNAL (programming language)OpticsPlanarDynamic rangeWavelengthAmplifierRayPhotodetectorPhysicsComputer scienceThin filmNanotechnologyChemistry

Abstract

fetched live from OpenAlex

A photoreceptor array that exploits the light sensitive bacteriorhodopsin (bR) films has been manufactured on a flexible indium-tin-oxide (ITO) coated plastic film using electrophoretic sedimentation technique (EPS). The effective sensing area of each photoreceptor is 2 x 2 mm (2), separated by 1 mm and arranged in a 4 x 4 array. A switched integrator with gain on the order of 10(10) is used to amplify the signal to a suitable level. When exposed to light, the differential response characteristic is attributed to charge displacement and recombination within bR molecules, as well as loading effects of the attached amplifier. The peak spectral response occurs at 568 nm and is linear over the tested light power range of 200 mu W to 12 mW. The response remains linear at other tested wavelengths, but with reduced amplitude. Initial tests have indicated that responsivity among all photoreceptors is greater than 71% of the average value, 465.25 mV/mW. The differential nature of the signal generated by bR makes it a suitable sensing material for vision applications such as motion detection. The prototype array demonstrates this property by employing Reichardt's delay-and-correlate algorithm. Furthermore, fabricating sensor arrays on flexible substrates introduces a new design approach that enables non-planar imaging surfaces.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.039
GPT teacher head0.283
Teacher spread0.244 · 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
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

Citations35
Published2008
Admission routes2
Has abstractyes

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Same venueIEEE Transactions on NanoBioscienceSame topicPhotoreceptor and optogenetics researchFrench-language works237,207