P‐130: A Full Screen Biometric Identification Approach for OLED Displays by Using Near‐Infrared OLED
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.
Bibliographic record
Abstract
In this paper, we propose a full screen biometric identification approach for organic light emitting diode (OLED) displays using a near infra‐red(NIR) OLED coupled to a large area thin film transistor (TFT) pixel sensing circuit. Preliminary estimates for photons propagating from the NIR OLED source and reflecting back to the subpixel are presented. Although the signal landing on the subpixel is small, it may be amplified by the large area active pixel sensor circuits integrated in the TFT layer. The proposed approach has the key advantage of compatibility with existing large area fabrication processes. Although there are still some open technical issues such as NIR OLED lifetime, responsivity and sensor characteristics, the proposed approach demonstrates the potential to implement a full screen biometric identification within a large area display.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it