Bayesian hierarchical models for mapping lung cancer mortality in Ontario
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
No Canadian affiliation. An affiliation-only frame — the usual design — would never have seen this work. It is one of the works that make the case for inverting the frame.
The three-model screen
all 1,000 screened works →All three models called this out of scope.
Dissertation on Bayesian disease mapping of Ontario lung cancer mortality; abstract is missing, and the title reads as applied epidemiology rather than research-on-research.
The title concerns mapping lung cancer mortality with Bayesian models, while the abstract is insufficient to add detail.
Uses Bayesian hierarchical models to map lung-cancer mortality; method-as-tool for epidemiology, not study of the method.
Abstract
grantor: University of Toronto
Stored with the screening record, where it is evidence for the labels above.
The record
- Venue
- TSpace
- Topic
- Hermeneutics and Narrative Identity
- Field
- Arts and Humanities
- Canadian institutions
- —
- Funders
- —
- Keywords
- Lung cancerBayesian probabilityStatisticsMedicineComputer scienceOncologyMathematics
- Has abstract in OpenAlex
- yes