PLOS Science Wednesday: Hi reddit, my name is Sarka Lisonkova and I published a study in PLOS Medicine showing mothers over 40 years have increasingly higher rates of adverse health outcomes – Ask me Anything!
Bibliographic record
Abstract
Hi Reddit, My name is Sarka Lisonkova and I am an Assistant Professor at the University of British Columbia, Department of Obstetrics and Gynaecology. My research focuses on risk factors and determinants of severe maternal morbidity. I recently published a study titled ‘Maternal age and severe maternal morbidity: a population-based retrospective cohort study’ in PLOS Medicine. This study shows that older mothers – aged 40 years or more – have increasingly higher rates of potentially life-threatening conditions including acute cardiac events, shock, acute renal failure, amniotic fluid embolism, and serious complications of obstetric interventions. Even though these serious complications are rare, our results provide important information for counseling to women who contemplate delaying childbirth until their forties. I will be answering your questions at 1pm ET. Ask me Anything! Don’t forget to follow me on Twitter @sarkalis.
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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 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.167 | 0.072 |
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".