VitalChart [EKG and breathing display device]
Bibliographic record
Abstract
As the Canadian population ages, the state of health care is an increasingly significant issue. The Canadian government already spends billions of dollars on health care and, in 2000-2001, the Medical Equipment Fund totaled $500 million. This represents growing market potential for medical devices that enhance the quality and improve the efficiency of health care.\nWe propose to implement an electrocardiogram (EKG) and breathing rate monitor on a Palm™ personal digital assistant (PDA). Our product, VitalChart, will capture vitals, then record, store, and allow the manipulation of the data in an easy-to-use graphical user interface (GUI). These features allow VitalChart to automate patient charting, improving the efficiency of health care professionals.\nThe VitalChart utilizes a Palm™ m500 series PDA as a user interface. Our software will display the heart monitor waveform and the breathing rate of the patient on the Palm™ and handle data manipulation and simple charting. Future developments include a web-based database system that allows users to log in via the Internet and download patient data. Additional features being considered include a temperature sensor and blood pressure module.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.164 | 0.080 |
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".