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Record W7110500649

Research in Manitoba Saves Infants

2019· report· en· W7110500649 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2019
Typereport
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsDiseaseIncidence (geometry)Work (physics)Health carePregnancy
DOInot available

Abstract

fetched live from OpenAlex

The cure to Rh disease, once considered very deadly, was discovered due to the combined efforts by researchers from the UK, Germany, the USA, and Canada. The pioneering activities and innovations spearheaded by Dr. Bruce Chown and Professor Marion Lewis and later refined by Drs. Jack Bowman, Reinhart Friesen, and Alvin Zipursky from Winnipeg contributed to the continuous decline in the prevalence and incidence of Rh disease in the 1950s and 1960s, and helped accelerate the development of an Rh immune globulin, WINRHO, which has reduced the risk of death in sensitized pregnancies to nearly zero. Manitoba pioneered the application of antenatal dosing to Rh-negative. Today, almost all Rh-negative mothers are screened in their perinatal stage and are treated with the Immune globulin as a part of standard of care. Research and development on the Immune globulin have further evolved to other pharmaceuticals. Another legacy of the pioneering work of clinician-researchers in Winnipeg from the 1940s to the 1970s still evident today was the development of research capacity in Manitoba. Specifically, there is now the ability to conduct biomedical research primarily on immunoglobulins and the establishment of the research infrastructure necessary to bring research discoveries to commercial applications. Leading the country in the production and application of the Immune globulin, WINRHO has helped generate health and economic impacts across Manitoba and Canada.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.978
Threshold uncertainty score0.554

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0050.001
Scholarly communication0.0030.001
Open science0.0020.004
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0390.008

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.

Opus teacher head0.107
GPT teacher head0.311
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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