Robotic Remote Controlled Stereo Slit Lamp
Bibliographic record
Abstract
PURPOSE: Our purpose was to develop a robotic remotely operated stereo slit lamp system allowing three-dimensional stereo viewing and recording of the patient's examination via local area network, Internet, and satellite. METHODS: A commercial slit lamp was modified to accept motors and servos to permit control of all optical and mechanical components of the device. The custom graphical user interface with dual high-resolution real-time stereoscopic imaging, control/position indicators, overview video, and audio were transmitted via local area network, Internet, and satellite. Under University of Miami Institutional Review Board authorization, Internet connectivity enabled multiple examiners to simultaneously view and control the slit lamp and to collaboratively discuss diagnosis and treatment options. The remote clinicians used a tablet, laptop, or desktop computer to view and control the slit lamp. RESULTS: The network, Internet, satellite-connected system was controllable from the United States, Europe, and Canada while acquiring high-resolution, real-time video in all subjects. Control of the slit lamp through Ethernet, WiFi, and 4G exhibited total system latencies of 464 ± 58, 483 ± 64, and 870 ± 66 milliseconds when transmitting within the continent, and Ethernet control exhibited a latency of 606 ± 130 milliseconds when transmitting between continents. High- and low-magnification images of healthy volunteers were acquired by a remote clinician. CONCLUSIONS: The robotic remotely operated stereo slit lamp system allows three-dimensional stereo viewing and recording of the patient's examination via local area network, Internet, and satellite. TRANSLATIONAL RELEVANCE: The robotic remotely controlled stereo slit lamp system enables remote examination of human subjects.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".