Bibliographic record
Abstract
The Alberta Telehealth Network uses a provincial scheduling system, which allows use of the network to be monitored via reporting procedures. We developed a province-wide costing model for videoconferencing in Alberta, including administrative, clinical and educational activities. In 2003, there were 212 different videoconferencing sites. During the year, 5766 videoconferencing sessions were provided and in these sessions the sites were connected to the network a total of 21,596 times. About 27% of the connections were from providing sites and about 73% of the connections were from receiving sites. On average, one site in the telehealth system was connected to another site about 100 times, and the average videoconferencing session included about 3.8 sites, varying from mainly two sites in clinical sessions to 4.2 sites in administrative sessions and 6.1 sites in educational sessions. The total cost of videoconferencing in Alberta for administrative, clinical and educational activities was about CA $5.74 million in 2003. About 52% of the annual cost was for educational sessions, 34% for administrative meetings and 14% for clinical consultations. The average cost of videoconferencing at a single site ranged from $223.48 (for providing clinical consultations) to $278.57 (for receiving educational sessions). The costing model provides information for decision-makers about the cost of videoconferencing activities and can be used in the development of a sustainable telehealth system in Alberta.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.005 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".