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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".