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Record W4306154298 · doi:10.1530/etj-22-0180

Pediatric thyroid cancer guidelines: challenges in stratifying care based on limited data

2022· article· en· W4306154298 on OpenAlexaff
Andrew J. Bauer, Jonathan D. Wasserman, Steven G. Waguespack

Bibliographic record

VenueEuropean Thyroid Journal · 2022
Typearticle
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersChildren's Hospital of Philadelphia
KeywordsMedicineThyroid cancerThyroid nodulesTask forceThyroidFamily medicinePediatricsInternal medicinePublic administration

Abstract

fetched live from OpenAlex

The 2022 European Thyroid Association Guidelines for the management of pediatric thyroid nodules and differentiated thyroid carcinoma (1) were developed by a task force comprising well-respected, expert clinicians with good representation of the European community, including several previously involved in authorship of country-specific guidelines from Poland (2), the United Kingdom (3), the Netherlands (4), and the United States (5). Van Santen and the guidelines committee are to be commended for their thoughtful and stringent review of the literature in an effort to optimize the care of pediatric patients diagnosed with thyroid nodules and thyroid cancer.

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)0.087
metaresearch head score (Gemma)0.351
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: Review · Consensus signal: none
Teacher disagreement score0.087
Threshold uncertainty score0.461

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0870.351
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0110.009
Science and technology studies0.0020.002
Scholarly communication0.0070.009
Open science0.0070.006
Research integrity0.0030.008
Insufficient payload (model declined to judge)0.0050.002

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 head0.304
GPT teacher head0.445
Teacher spread0.142 · 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
GenreReview

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

Citations7
Published2022
Admission routes1
Has abstractyes

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