Introduction
Bibliographic record
Abstract
Optical wireless communication is an emerging and dynamic research and development area that has generated a vast number of interesting solutions to very complicated communication challenges. For example, high data rate, high capacity and minimum interference links for short-range communication for inter-building communication, computer-to-computer communication, or sensor networks. At the opposite extreme is a long-range link in the order of millions of kilometers in the new mission to Mars and other solar system planets. It is important to mention that optical wireless communication is one of the oldest methods that humanity has used for communication. In prehistoric times humans used fire and smoke to communicate; later in history, Roman optical heliographs and Sumerians signalling towers were the communication systems of these empires. An analogous technology was used by Napoleonic Signalling Towers and “recently” by the light photo-phone of Alexander Graham Bell back in the 1880s. Obviously, the data rate, quality of service delivered, and transceiver technologies employed have improved greatly from those early optical wireless technologies. In its many applications, optical wireless communication links have already succeeded in becoming part of our everyday lives at our homes and offices. Optical wireless products are already well familiar, ranging from visible-light communication (VLC), TV remote control to IrDA ports that currently have a worldwide installed base of hundreds of million of units with tens of percent annual growth. Optical wireless is also widely available on personal computers, peripherals, embedded systems and devices of all types, terrestrial and in-building optical wireless LANs, network of sensors, and inter-satellite link applications.
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.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.439 | 0.332 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".