Limited output transcranial electrical stimulation 2023 (LOTES-2023): Updates on engineering principles, regulatory statutes, and industry standards for wellness, over-the-counter, or prescription devices with low risk
Bibliographic record
Abstract
The objective and scope of this Limited Output Transcranial Electrical Stimulation 2023 (LOTES-2023) guidance is to update the previous LOTES-2017 guidance. These documents should therefore be considered together. The LOTES provides a clearly articulated and transparent framework for the design of devices providing limited output (specified low-intensity range) transcranial electrical stimulation for a variety of intended uses. These guidelines can inform trial design and regulatory decisions, but most directly inform manufacturer activities - and hence were presented in LOTES-2017 as "Voluntary industry standard for compliance controlled limited output tES devices". In LOTES-2023 we emphasize that these standards are largely aligned across international standards and national regulations (including those in USA, EU, and South Korea), and so might be better understood as "Industry standards for compliance controlled limited output tES devices". LOTES-2023 is therefore updated to reflect a consensus among emerging international standards, as well as best available scientific evidence. "Warnings" and "Precautions" are updated to align with current biomedical evidence and applications. LOTES standards applied to a constrained device dose range, but within this dose range and for different use-cases, manufacturers are responsible to conduct device-specific risk management.
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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 | 0.030 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.013 | 0.008 |
| Insufficient payload (model declined to judge) | 0.015 | 0.011 |
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".