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Record W3009344988 · doi:10.1503/cmaj.190777

Clinical guideline for homeless and vulnerably housed people, and people with lived homelessness experience

2020· article· en· W3009344988 on OpenAlexafffundvenue
Kevin Pottie, Claire Kendall, Tim Aubry, Olivia Magwood, Anne Andermann, Ginetta Salvalaggio, David Ponka, Gary Bloch, Vanessa Brcic, Eric Agbata, Kednapa Thavorn, Terry Hannigan, Andrew Bond, Susan Crouse, Ritika Goel, Esther S. Shoemaker, Jean Zhuo Wang, Sebastian Mott, Harneel Kaur, Christine Mathew, Syeda Shanza Hashmi, Ammar Saad, Thomas Piggott, Neil Arya, Nicole Kozloff, Michaela Beder, Dale Guenter, Wendy Muckle, Stephen W. Hwang, Vicky Stergiopoulos, Peter Tugwell

Bibliographic record

VenueCanadian Medical Association Journal · 2020
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsCanadian Medical AssociationCanadian Public Health AssociationCollege of Family Physicians of CanadaCanadian Association of Emergency PhysiciansCanadian Nurses Association
FundersCanadian Medical AssociationPublic Health AgencyPublic Health Agency of Canada
KeywordsAusterityGentrificationGuidelineGerontologySociologyMedicinePsychologyPolitical scienceEconomic growthEconomics

Abstract

fetched live from OpenAlex

[See related article at [www.cmaj.ca/lookup/doi/10.1503/cmaj.200199][2]][2] KEY POINTS Homeless and vulnerably housed populations are heterogeneous[1][2] and continue to grow in numbers in urban and rural settings as forces of urbanization collide with gentrification and austerity policies.[2][3]

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)0.002
metaresearch head score (Gemma)0.012
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: Methods · Consensus signal: none
Teacher disagreement score0.909
Threshold uncertainty score0.182

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.002
Science and technology studies0.0040.001
Scholarly communication0.0020.003
Open science0.0040.002
Research integrity0.0080.006
Insufficient payload (model declined to judge)0.0170.007

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 head0.385
Teacher spread0.344 · 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
GenreMethods

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

Citations101
Published2020
Admission routes3
Has abstractyes

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Same venueCanadian Medical Association JournalSame topicHomelessness and Social IssuesFrench-language works237,207