Bibliographic record
Abstract
To the Editor Dr. Story is to be commended for his recent description1 of a clinically useful approach to blood gas interpretation that combines the base excess and Stewart models, and that does so using only 4 simple equations. He expresses the hope that readers will try this method for “the next ten patients … requiring arterial blood gas analysis.” Because calculating even 4 equations can be daunting in the midst of complex patient management, I have created a calculator app to do this part of the work. It is a Web app that can be used on any device (smart phone, tablet, or computer) that is capable of accessing the Internet. To open it, point your Web browser to the following address: www.abgst.altervista.org. It is my hope that the availability of this easy-to-use cognitive aid will encourage practitioners to try Dr. Story’s approach. John H. P. Friesen, MDDepartment of Anesthesia & Perioperative MedicineUniversity of ManitobaWinnipeg, Manitoba, Canada[email protected]
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.004 |
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; both teacher heads agree on what is shown here.
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".