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Record W4410864868 · doi:10.1093/jnci/djaf096

Response to Siegel, Kratzer, Smith et al.

2025· article· en· W4410864868 on OpenAlexaff
Archie Bleyer, Lynn A. G. Ries, Danielle B. Cameron, Sara A. Mansfield, Stuart E. Siegel, Ronald D. Barr

Bibliographic record

VenueJNCI Journal of the National Cancer Institute · 2025
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPhilosophy

Abstract

fetched live from OpenAlex

The American Cancer Society (ACS) Correspondence1 concludes that our “title, premise, and conclusion are conjectures” that “jeopardize research to discover the etiology behind” the increasing colorectal cancer (CRC) incidence in 45-49-year-olds that the ACS includes in their CRC screening guidelines.2,3 However, our title states “the young” and not 45-49-year-olds and includes “all cancer” and not just CRC. Our focus was on adolescents and young adults (AYAs, age 15-39) and to a lesser degree on <15-year-olds. We did not cite 45-49-year-olds or depict this age group except in one figure that has all 5-year age groups from birth to 85. Our premise was that reclassification of carcinoid tumors as malignant “artifactually” increases colon, colorectal, and all cancer incidence if the appendix is included, and especially in AYAs and younger patients. We concluded that “the younger the age the greater the appendix artifact” and “a significant proportion of the overall cancer increase in AYAs during the last decade, as much as 32%, is attributable to the appendix cancer reclassification” and that “appendix tumors should … not be included.”

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)0.006
metaresearch head score (Gemma)0.038
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.035
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.038
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0040.004
Open science0.0040.003
Research integrity0.0350.035
Insufficient payload (model declined to judge)0.0250.019

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 head0.041
GPT teacher head0.381
Teacher spread0.341 · 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
GenreCommentary

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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJNCI Journal of the National Cancer InstituteSame topicColorectal Cancer Screening and DetectionFrench-language works237,207