The Spot* System for Flexible Personal Heating and Cooling
Bibliographic record
Abstract
SPOT* is a cost-effective, legacy-compatible, flexible system for personalized heating and cooling. It senses occupancy and worker comfort uses the Predicted Mean Vote equation to determine worker comfort. It then actuates a fan or a heater to adjust the comfort level so that it lies between -0.5 and +0.5 in the ASHRAE comfort scale. SPOT* greatly reduces costs compared to our prior SPOT and SPOT+ systems by using the fewest possible sensors and a lightweight compute engine that can be located in the cloud. Moreover, SPOT* provides both cooling and heating using a speed-controlled desktop fan, rather than only controlling heating using a radiant heater. Finally, SPOT* is less intrusive in that it does not use a camera. The per-user cost for SPOT* is about $185 compared to $1000 for SPOT/SPOT+. We find that in a preliminary deployment, SPOT* is able to improve user comfort by 78% over legacy systems alone.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.059 | 0.013 |
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".