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Record W4386003093 · doi:10.1136/bmjopen-2023-074710

Cancer risk factors and access to cancer prevention services for people experiencing homelessness: a scoping review protocol

2023· review· en· W4386003093 on OpenAlexaff
Tobias Schiffler, Maren Jeleff, Alejandro Gil-Salmerón, Lin Yang, Sandra Haider, Felipe Barreto Schuch, Igor Grabovac

Bibliographic record

VenueBMJ Open · 2023
Typereview
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of CalgaryAlberta Health Services
FundersH2020 Societal ChallengesUniversität WienMedizinische Universität WienEuropean Commission
KeywordsCINAHLMedicineGrey literatureScopusProtocol (science)MEDLINEData extractionPopulationFamily medicineMedical educationAlternative medicineNursingPsychological interventionEnvironmental healthPathology

Abstract

fetched live from OpenAlex

INTRODUCTION: Homelessness is a complex social issue that significantly impairs the health of those affected. People experiencing homelessness (PEH) have a higher prevalence of adverse health outcomes, including premature mortality, compared with the general population, with cancer being the second-leading cause of death. The objective of this scoping review is to map the evidence to assess the exposure of PEH to known cancer risk factors and identify barriers and facilitators PEH experience in accessing cancer prevention services. METHODS AND ANALYSIS: This scoping review will be conducted in line with the Joanna Briggs Institute guidelines for scoping reviews. For a time window from the date of database establishment until 20 February 2023, the research team will create a detailed search strategy and apply it to the following databases: CINAHL, Embase, Global Index Medicus, PubMed, Scopus and Web of Science. In addition, we will search OpenGrey and Google for grey literature and contact non-governmental organisations to request relevant reports. In the first stage, eligibility criteria will be assessed through a blinded title/abstract assessment, and following this assessment, a full-text screening will be performed. Subsequently, the research team will perform the data extraction and synthesise all relevant information in relation to the scoping review question. ETHICS AND DISSEMINATION: As this protocol does not involve gathering primary data, ethical approval is not necessary. The results of this review will be published in a peer-reviewed journal and on institutional websites.

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)0.104
metaresearch head score (Gemma)0.073
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: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.104
Threshold uncertainty score0.552

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1040.073
Meta-epidemiology (narrow)0.0040.005
Meta-epidemiology (broad)0.0110.011
Bibliometrics0.0160.012
Science and technology studies0.0050.005
Scholarly communication0.0080.008
Open science0.0060.007
Research integrity0.0100.006
Insufficient payload (model declined to judge)0.0740.020

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 head0.374
GPT teacher head0.655
Teacher spread0.281 · 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
GenreProtocol

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

Citations3
Published2023
Admission routes1
Has abstractyes

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