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Record W4417278853 · doi:10.5194/ica-abs-10-66-2025

Spatial Analysis of HPV Cancer Mortality in Persistent Poverty Counties in the US (1999-2020)

2025· article· en· W4417278853 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAbstracts of the ICA · 2025
Typearticle
Languageen
FieldMedicine
TopicData-Driven Disease Surveillance
Canadian institutionsEsri (Canada)
Fundersnot available
KeywordsPovertyCervical cancerPopulationCancerPublic health

Abstract

fetched live from OpenAlex

Human papillomavirus (HPV) is the most common sexually transmitted infection in the United States, with nearly 90% of men and 80% of women contracting an HPV strain at some point in their lives.Of these infections, approximately 50% involve high-risk, cancer-causing strains (Vickers et al., 2019).While many HPV infections are low-risk and resolve on their own, certain high-risk strains are linked to cancer development.Data from the Centers for Disease Control and Prevention (CDC) for 2017-2021 reports over 47,100 new cases of HPV-related cancer annually (Centers for Disease Control and Prevention, 2024).Globally, HPV accounts for 5% of all cancers (National Cancer Institute, 2023).Cervical cancer is the fourth most common cancer in women globally and caused an estimated 342,000 deaths in 2020 (World Health Organization, 2024).Cervical cancer is the most common HPV-associated cancer among women, and oropharyngeal cancers (cancers of the back of the throat, including the base of the tongue and tonsils) are the most common among men in the US (Centers for Disease Control and Prevention, 2024).

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.968

Codex and Gemma teacher scores by category

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

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 head0.014
GPT teacher head0.299
Teacher spread0.285 · 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