Reasearch on TCP State Machine Reduction in Embedded Internet Kernel
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 Embedded Internet (EI) environment there are limited resources, so it is very difficult to realize a Internet in EI environment. In general some high performance processor and memory are used to solve the problem. It is clearly is the wrong way as it incurs additional development time, testing time and price. In this paper a proper method is presented which is based on TCP state machine reduction. In TCP/IP protocol suite TCP is the most complex protocol and consumed most resources. We delete unimportant and unnecessarily state in EI environment and simplify complex relations. All these reduction are complete transparent for user because the interfaces are untouched. According to the reduction principle proposed in paper we realize an mini EI kernel in a 8 bit processor, in this kernel there are full function Web Server and correlative protocols.
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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 | 0.000 |
| 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