Bibliographic record
Abstract
We propose the use of multiple sensors of different sensitivity that simultaneously sense the same signal. Outputs of these sensors are then combined in a way that allows the simultaneous sensing of large-signal and small-signal phenomena. This sensing methodology is applied to the andantephone, a musical instrument that allows a player to physically step through the notes of a song as if they were walking along the song's timeline. When you stop walking the music stops. If you walk faster the music plays faster. A new, more expressive design of andantephone was created using a wideband complementary set of geophones to detect seismic waves transmitted from human footsteps. Each tile in the andantephone has one or more high-frequency piezoelectric geophones that respond to small-signals, as well as one or more low-frequency carbon geophones that respond to large-signals. These sensors are subsequently connected to a real-time frequency-shifting system that shifts each geophone's output to the correct musical pitch or chord for a particular note in a song. The proposed HDR sensing principle may be applied to many different sensing scenarios.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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 teacher head, 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".