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Ringworm and Irradiation

2022· book· en· W4213418559 on OpenAlexaboutno aff
Shifra Shvarts, Siegal Sadetzki

Bibliographic record

VenueOxford University Press eBooks · 2022
Typebook
Languageen
FieldMedicine
TopicCervical Cancer and HPV Research
Canadian institutionsnot available
Fundersnot available
KeywordsTinea capitisMedicineScalpDermatologyGriseofulvinPopulationRadiation therapyThyroid cancerCancerPediatricsEnvironmental healthSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Abstract The practice of using x-rays for the medical treatment of benign diseases began in the 1920s and peaked in the 1940s and 1950s. Radiation therapy was considered good medical practice during the first decades of the 20th century and was very effective at controlling and eliminating ringworm (tinea capitis), an epidemic that was spread mainly among children. Results were often immediate. In the United States, Canada, Europe, Australia, the Middle East, and North Africa, hundreds of thousands of children were treated with radiation therapy for ringworm of the scalp. X-ray treatment gradually came to an end in the 1960s when other effective oral treatments were developed (e.g., griseofulvin for ringworm). In parallel, studies started to suggest that radiation exposure, especially in childhood, might increase the risk for developing blood malignancies, benign and malignant tumors of the thyroid gland, and leukemia. This volume discusses the use of irradiation for the treatment of ringworm in different countries in the first half of the 20th century; the latent risk for the development of tumors, malignancies, thyroid cancer, brain tumors, and other health effects among the exposed population; media coverage; and the initiatives of the National Cancer Institute to launch a nationwide campaign warning the medical community and public about the late health effects of ionizing radiation

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)0.000
metaresearch head score (Gemma)0.000
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 score0.054
Threshold uncertainty score0.180

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0540.020

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 head0.031
GPT teacher head0.252
Teacher spread0.221 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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