Bibliographic record
Abstract
My doctors said it was impossible... After all the radiation and chemotherapy, I was told that I would not be able to have children. We searched for a surrogate, we looked into adoption… it seemed so hopeless and then, it happened. I was a bit nervous to tell my program because I am the first University of Alberta cardiac surgery resident to become pregnant. I did not expect their response, “Michiko, our job is to create excellent surgeons. Being an excellent surgeon does not just include being technically skilled. It involves being well rounded and excelling at all areas of life. If part of your life involves being a mother and having a family, then we are here to support and encourage you all the way.” I am proud to share that I am the mother of a beautiful baby boy. "Welcome to Motherhood” is an illustrative photograph that represents my experience as a surgical resident and, at the time, a soon to be mother. I am the first cardiac surgery resident at the University of Alberta to become pregnant. I am so thankful to my program for all their support and encouragement throughout my pregnancy and after, when I entered motherhood. The relevance to cardiovascular science is that I feel it is important to acknowledge my cardiac surgery programs response to my pregnancy announcement. In a male dominated field with no experience of pregnant trainees, they did an incredible job to support and encourage me along the way.
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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.015 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.083 | 0.024 |
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".