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Record W2888670337 · doi:10.1177/1093526618794831

Pioneer in Pediatric Pathology: William A (Bill) Newton Jr (1923–)

2018· article· en· W2888670337 on OpenAlexaff
James R. Wright, Peter B. Baker, Hiroyuki Shimada

Bibliographic record

VenuePediatric and Developmental Pathology · 2018
Typearticle
Languageen
FieldMedicine
TopicNeuroblastoma Research and Treatments
Canadian institutionsCalgary Laboratory ServicesAlberta Children's HospitalUniversity of Calgary
Fundersnot available
KeywordsPediatric oncologyMedicineAudience measurementAnatomical pathologySurgical pathologyClinical pathologyFamily medicinePathologyPediatricsGeneral surgeryCancerInternal medicine

Abstract

fetched live from OpenAlex

William A (Bill) Newton Jr practiced pediatric pathology and hematology/oncology at Children's Hospital of Columbus, Ohio, for over 40 years starting in 1952. Newton was an original member of the Pediatric Pathology Club, which preceded the Society for Pediatric Pathology, and was its president from 1968 to 1969. He published important independent observations in pediatric pathology, helped establish systematic cooperative pediatric tumor pathology review by experts, became an acclaimed expert on the diagnosis of rhabdomyosarcoma, was a critical contributor to many pediatric oncology clinical trials, made important early contributions to tumor banking in pediatrics, and trained numerous pediatric pathology and pediatric oncology fellows. Finally, he concluded his career as a humanitarian, leading important volunteer work aimed at improving pediatric cancer care in China. This most interesting pediatric pathologist was simultaneously a Brigadier General in the U.S. Army. Bill Newton's life and career, which is reviewed in detail here, should be of immense interest and an inspiration to the Pediatric & Developmental Pathology readership.

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)0.004
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: none
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.007
Insufficient payload (model declined to judge)0.0080.005

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 head0.017
GPT teacher head0.273
Teacher spread0.257 · 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

Citations2
Published2018
Admission routes1
Has abstractyes

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