Bibliographic record
Abstract
Lightweight group meetings are opportunistic, ad-hoc, or lightly planned gatherings characterized by the informal nature of their members and their tasks. Critically, they must be very easy to set up and maintain over time. We contribute the design of Come Together, a system that supports lightweight, persistent meetings between distance-separated people. Its design is theoretically motivated by the Locales Framework, with features derived from the best of Instant Messengers and the Community Bar. Its main motivation is that any action must be simple and fast to do if it is to support lightweight group meetings. In particular, Come Together represents both people and their things as media items, which - unlike prior systems - can be quickly brought together to form an ad hoc place. Places, which are persistent, can be presented in a variety of forms (e.g., as a stand-alone window, or as an element in a sidebar), with interaction mechanisms that let a person quickly adjust the degree of awareness he or she wishes to maintain of the place and its contents. Somewhat akin to buddy lists, a console collects all people, artifacts, and places, where users can select them to rapidly compose meeting places.
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.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.056 | 0.025 |
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".