Bibliographic record
Abstract
With the rapid development in the areas of multisensory hard- and software and the emergence of Tactile Internet, new media such as haptics, smell, olfaction, etc., nowadays, play a prominent role in making virtual objects physically tangible in a collaborative and/or networked virtual environment. By allowing users to feel each other's presence and physically manipulate objects from their interacted environments within 1 ms. The Tactile Internet facilitates fast multimodal interactions with multisensory information over the 5G network. 1 ms is a critical threshold in human perception of tactile response. For auditory response, this threshold is 100 ms and for visual response, it is 10 ms, which means delays above these thresholds are within the latency limit sensed by the human brain. In 4G, the round trip latency is 25 ms for an ideal environment. Clearly, that indicates 4G is not able to meet the requirements of tactile response. For this reason, the efforts to reduce latency in 5G are critical for Tactile Internet. Low-latency communications will also enable other digital twins’ applications such as real-time control of smart grid, self-driving car, and so on.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.003 |
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".