Bibliographic record
Abstract
Dr. Kateryna Metersky is an Assistant Professor at the Daphne Cockwell School of Nursing at Ryerson University in Toronto, Canada. She is also a practicing nurse in General Internal Medicine at University Health Network - Toronto Western Hospital. As an educator, she continuously strives to develop innovative ways to enrich the educational experience for her students, and one such method is through the use of poetry in the classroom. Dr. Metersky enjoys composing poetry to explain difficult and theoretical concepts to nursing and interprofessional students, as well as patients in her care. She crafted this poem to help students understand what it is like for patients to live with heart disease. Dr. Metersky received the diagnosis of non-sustained ventricular tachycardia in 2019 and has experienced uncertainty living with this chronic illness. To this day, Dr. Metersky is still seeking a solution for this diagnosis that will help her live well with this condition.
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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.011 |
| Insufficient payload (model declined to judge) | 0.029 | 0.014 |
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".