Secure and resilient data printed on paper
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
Transmission and printing of sensitive information requires both data security, and protection against random and burst errors. This paper describes a technique that achieves two objectives: secure and reliable transmission of information; and integrity of the original information printed on paper. Information printed on paper is prone to burst and random errors. Resilience of the information to such errors is obtained by introducing redundancy into the original data using forward error correcting codes. We have selected a concatenation of a Reed-Solomon (RS) code, interleaved with a self-orthogonal majority decodable convolutional code. To measure the performance of the concatenated code, the bit error rate against signal to noise ratio of the code is compared with codes of equivalent rate (e.g., RS code alone) and with the unencoded data. Security of the printed data can be achieved through encryption. We have selected a probabilistic encryption scheme of messages to achieve an increased security against reverse engineering of the printed pattern. A new document signature extraction scheme based on fractal signal processing is described. Such a signature is then included with the document in the security pattern.
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.
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 | 0.000 |
| 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