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Record W2116661571 · doi:10.2310/7750.2014.13162

Skin Cancer (Basal Cell Carcinoma, Squamous Cell Carcinoma, and Malignant Melanoma): New Cases, Treatment Practice, and Health Care Costs in New Brunswick, Canada, 2002–2010

2014· article· en· W2116661571 on OpenAlexaffabout
Wilfred Pilgrim, Robert C. Hayes, Dana W. Hanson, Bin Zhang, Bonnie Boudreau, Suzanne Leonfellner

Bibliographic record

VenueJournal of Cutaneous Medicine and Surgery · 2014
Typearticle
Languageen
FieldMedicine
TopicNonmelanoma Skin Cancer Studies
Canadian institutionsGovernment of New Brunswick
Fundersnot available
KeywordsSkin cancerMedicineBasal cell carcinomaHealth careBasal cellIncidence (geometry)EpidemiologyCancerCancer registryDermatologyFamily medicineMelanomaInternal medicineCancer research

Abstract

fetched live from OpenAlex

BACKGROUND: In Canada, there is no formal process for registering nonmelanoma skin cancer (NMSC); thus, the epidemiology, treatment practices, and associated health costs are not well known. OBJECTIVES: To investigate trends in new cases of skin cancer, treatment practices, and health care costs in New Brunswick, Canada. METHODS: Data were extracted from the Provincial Cancer Registry and New Brunswick administrative health databases for 2002-2010. RESULTS: New cases: Basal Cell Carcinoma (BCC) was the most common skin cancer diagnosed, and incidence rates significantly increased between 1992 and 2010.Treatment practice: Dermatologists managed the majority (45%) of the overall skin cancer treatments.Health care costs: NMSC accounted for ∼80% of the health care costs for skin cancer and was dominated by BCC. CONCLUSIONS: Development of best practice treatment guidelines for NMSC in New Brunswick would improve future health care efficiencies, and standard protocols for registering new cases of NMSC in Canada would strengthen surveillance and reporting capacity.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.216
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
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 head0.022
GPT teacher head0.277
Teacher spread0.255 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations11
Published2014
Admission routes2
Has abstractyes

Explore more

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