Bioelectronic Imaging Array Based on Bacteriorhodopsin Film
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".