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Record W4390525903

I Never Had a Choice: My Lifelong Struggle With Polio

2020· article· en· W4390525903 on OpenAlexaboutno aff
Cathy Casares Reynolds

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2020
Typearticle
Languageen
FieldMedicine
TopicMedicine and Dermatology Studies History
Canadian institutionsnot available
Fundersnot available
KeywordsPoliomyelitisPsychologyMedicineVirology
DOInot available

Abstract

fetched live from OpenAlex

In 1921 on Campobello Island, Franklin D. Roosevelt began his legacy, not as the 32nd president of the United States nor as the man who would lead the Allied nations to victory over Nazi Germany, but as the most famous survivor of polio. While on vacation at his family’s home in New Brunswick, Canada, FDR’s legs became progressively weaker, and by the third day, they could no longer support his weight. After several misdiagnoses, he eventually discovered he had contracted infantile paralysis, i.e., polio. As the name suggests, the disease typically presents during infancy, and most children develop immunity before they turn 5; however, for those who are afflicted, polio can cause lifelong paralysis or death. Long before COVID-19, polio was the most feared disease in the world. In 1952 alone, before a polio vaccine was available, almost 60,000 American children were infected, thousands were paralyzed, and more than 3,000 perished. Three years later, the United States began widespread inoculation for polio, and by 1979, it had been eradicated across the country. Since then, the vaccine has been so effective, some have begun to question its necessity. Few people today know someone personally who has been stricken with this horrific disease. No longer is polio what took the life of a loved one or left a neighbor unable to walk. Polio is now a theoretical concept, and the hundreds of thousands of lives taken or disabled have been distilled to “why FDR was in a wheelchair."

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)0.008
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.029
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0290.019
Scholarly communication0.0130.014
Open science0.0020.009
Research integrity0.0080.048
Insufficient payload (model declined to judge)0.0070.003

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 head0.263
GPT teacher head0.544
Teacher spread0.281 · 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 designQualitative
Domainnot available
GenreEmpirical

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
Published2020
Admission routes1
Has abstractyes

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