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Record W4321083903 · doi:10.4018/ijagr.318138

IJAGR at the International Medical Symposium Geography 2022 Edinburgh, Scotland

2023· article· en· W4321083903 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
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.

Bibliographic record

VenueInternational Journal of Applied Geospatial Research · 2023
Typearticle
Languageen
FieldMedicine
TopicData-Driven Disease Surveillance
Canadian institutionsnot available
FundersUniversity of TorontoQueen's UniversityUniversity of North Carolina at Chapel HillAppalachian State University
KeywordsLibrary scienceGeospatial analysisHealth geographyGeographyState (computer science)Event (particle physics)HistoryMedia studiesMedicineCartographySociologyPublic healthInternational healthPathologyHealth policy

Abstract

fetched live from OpenAlex

Donald Albert (co-Editor-in-Chief) from Sam Houston State University and Dhitinut Ratnapradipa (Associate Editor) from Creighton University participated in the 19th International Medical Symposium Geography (IMGS) from June 19-June 24, 2022, in Edinburgh, Scotland. The event operated out of the Royal College of Surgeons located in the Old Town of Edinburgh. This historic venue provided an appropriate setting to contemplate patterns of health and disease. Jamie Pearce and Niamh Shortt (University of Edinburgh) were co-Chairs of the IMGS 2022. The authors' poster abstract was entitled, “The International Journal of Applied Geospatial Research: Temporal Metrics and Coverage of Medical Geography, 2010-2021.”

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.112
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.028
GPT teacher head0.376
Teacher spread0.347 · 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