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Record W2991862006 · doi:10.23889/ijpds.v4i1.1124

Concept Dictionary and Glossary at MCHP

2019· article· en· W2991862006 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal for Population Data Science · 2019
Typearticle
Languageen
FieldHealth Professions
TopicMedical Coding and Health Information
Canadian institutionsUniversity of ManitobaManitoba Health
Fundersnot available
KeywordsGlossaryDocumentationComputer scienceConsistency (knowledge bases)GlobeData scienceGovernment (linguistics)Knowledge managementTerminologyWorld Wide WebArtificial intelligenceLinguisticsPsychology

Abstract

fetched live from OpenAlex

The Manitoba Centre for Health Policy's Concept Dictionary and Glossary, and the Data Repository they document, broaden the analytic possibilities associated with administrative data. The aim of the Repository is to describe and explain patterns of health care and illness, while the Concept Dictionary and Glossary create consistency in documenting research methodologies. The Concept Dictionary alone contains detailed operational definitions and programming code for measures used in MCHP research that are reusable in future projects. Making these tools available on the internet allows reaching a heterogeneous audience of academic and government health service partners, epidemiologists, planners, programmers, clinicians, and students extending around the globe. They aid in the retention of corporate knowledge, facilitate researcher/analyst communication, and enhance the Centre's knowledge translation activities. Such documentation has saved countless hours for programmers, analysts and researchers who frequently need to tread paths previously taken by others.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.289
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.318
GPT teacher head0.551
Teacher spread0.233 · 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