Thinking Outside the Inbox: Use of Slack in Clinical Groups as a Collaborative Team Communication Platform
Bibliographic record
Abstract
<p>[para. 1]: "Academic faculty commonly collaborate across organizations located in multiple time zones, rendering in-person communication impractical. Furthermore, local access to content experts may be limited at many institutions, and multiple competing commitments may preclude attendance at relevant networking events. This is especially true during public health crises such as the COVID-19 pandemic, which has accelerated the incorporation of digital alternatives into workflow. Therefore, it is important for teams to develop easily accessible, reliable, and cloud-based collaborative tools to facilitate communication. Although e-mail remains a viable option for short, intermittent communications, the time spent reading and responding to e-mails among larger teams discussing disparate topics may impair productivity. E-mail creates multiple synchronous discussions, making it difficult for individual team members to follow and distinguish topics or projects. At academic medical centers, high volumes of e-mails risk effective team communication due to important e-mails being overlooked or inadvertently deleted."</p>
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 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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".