Towards Quality of Experience in Advanced Collaborative Environments
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
Collaborative environments have the potential of truly supporting distributed teams but there are still a number of barriers preventing seamless collaboration. These barriers are a result of problems in the following four domains: 1) a lack of understanding of the tasks that people perform when they are collaborating; 2) a lack of understanding and fulfillment of users ' needs during collaborations; 3) the high complexity of collaboration services; and 4) limited access to a wide variety of technologies for use in complex, heterogeneous, and dynamic environments. The goal of our Advanced Collaborative Environment (ACE) project is to support seamless collaboration by removing these barriers and improving the users ' Quality of Experience (QoE). This paper describes our view of a QoE-ACE architecture of the future, an architecture that takes into account not only available and emerging technologies, but also the users, their individual needs, and the uniqueness of the tasks they set out to pursue. 1.
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 | 0.000 | 0.001 |
| 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) | 0.001 | 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