Retraction: Self-attention fusion for audiovisual emotion recognition with incomplete data
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This article has been retracted by Darcy & Roy Press following an allegation that this article is an almost direct copy of another published work. Darcy & Roy Press has investigated in line with the COPE guidelines, and agree the evidence shows this work was first published elsewhere by different authors [1]. The authors have not been able to provide a satisfactory explanation for such substantial overlap. As a result, in line with the COPE retraction guidelines, Darcy & Roy Press retracts this article for plagiarism. Despite responding in earlier stages of the investigation, the authors have not commented on the wording of the retraction notice. Retraction published: September 02, 2025. Reference [1] K. Chumachenko, A. Iosifidis and M. Gabbouj, "Self-attention fusion for audiovisual emotion recognition with incomplete data," 2022 26th International Conference on Pattern Recognition (ICPR), Montreal, QC, Canada, 2022, pp. 2822-2828, doi: 10.1109/ICPR56361.2022.9956592.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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