A Method for Canines to Concentrate Presented Stimuli by Seamlessly Switching between Real-time and Recorded Video Using Automatic Curtain Manipulation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We aim to elucidate canine super-sensing, which is the ability to notice changes in human emotion. If we can elucidate canine super-sensing, we believe that it can be applied to various fields as a new sensing principle. For the purpose of elucidation, we have fabricated a device that presents stimuli to multiple canine senses. However, with the previously proposed method, the canine could not concentrate on the presented information due to the discomfort of the visual stimuli, and the canine did not concentrate on the presented stimuli for 30 seconds. In this paper, we describe how we improved the method of presenting visual information and automated the apparatus to shorten the experimental time.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it