Study on the Relationship Between Quality and Acceptability Annoyance (AccAnn) of UGC Videos
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 study the relationship between acceptability/annoyance rating and traditional MOS quality ratings of UGC videos. Acceptability/annoyance is a key concept for evaluating services, as it classify whether the delivered service quality falls into acceptable, annoying but acceptable, or not acceptable. This relates to the willingness of users to use those services. While audiovisual quality estimation models have a long research history, the translation of these quality scores to acceptability and willingness to use the services has only been weakly studied. In this work, a new dataset was then created to evaluate both quality and the acceptability/annoyance of videos. Different state-of-the-art quality prediction models videos were evaluated at predicting quality of UGC videos. Furthermore, performance at predicting acceptability/annoyance of videos was also tested.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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