Waning of Measles Antibody Titers in Young Infants
Bibliographic record
Abstract
Source: Science M, Savage R, Severini A, et al. Measles antibody levels in young infants. Pediatrics. 2019; 144( 6): e20190630; doi: 10.1542/peds.2019-0630[OpenUrl][1][Abstract/FREE Full Text][2] Investigators from multiple institutions in Canada conducted a retrospective study to assess immunity to measles among infants during the first 12 months of life in an area where measles has been eliminated due to vaccination. For the study, the authors assayed residual sera from infants <12 months of age seen at The Hospital for Sick Children, Toronto, Canada, between 2014 and 2016. The medical records of infants with available sera were reviewed; only those who had been born at ≥37 weeks’ gestation were included. Infants who had an immunodeficiency, had underlying conditions associated with antibody loss, had received IV or IM immune globulin or blood transfusions, or had a history of measles or measles … [1]: {openurl}?query=rft.jtitle%253DPediatrics%26rft_id%253Dinfo%253Adoi%252F10.1542%252Fpeds.2019-0630%26rft_id%253Dinfo%253Apmid%252F31753911%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/ijlink?linkType=ABST&journalCode=pediatrics&resid=144/6/e20190630&atom=%2Faapgrand%2F43%2F3%2F30.atom
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".