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
THIS ARTICLE INTRODUCES THEORETICAL and analytical tools for research involving musical emotion or musical change. We describe techniques for visualizing and analyzing data drawn from timevarying processes, such as continuous tension judgments, movement tracking, and performance tempo curves. Functional Data Analysis tools are demonstrated with real-time judgments of musical tension (a proxy for musical affect) to reveal patterns of tension and resolution in a listener's experience. The derivatives of tension judgment curves are shown to change with cycles of expectation and release in music, indexing the dynamics of musical tension. We explore notions of potential energy and kinetic energy in music and propose that affective energy is stored or released in the listener as musical tension increases and decreases. Differential calculus (and related concepts) are introduced as tools for the analysis of temporal dynamics in musical performances, and phase-plane plots are described as a means to quantify and to visualize musical change.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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