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Record W7061479031

Regional Medical Campuses: A New Classification System

2014· article· en· W7061479031 on OpenAlexaboutno aff

Bibliographic record

VenueVCU Scholars Compass (Virginia Commonwealth University) · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGyrotron and Vacuum Electronics Research
Canadian institutionsnot available
FundersSchool of Medicine, Virginia Commonwealth University
KeywordsNucleofectionFusible alloyHyporeflexiaArticular cartilage damageDiafiltrationGestational period
DOInot available

Abstract

fetched live from OpenAlex

There is burgeoning belief that regional medical campuses (RMCs) are a significant part of the narrative about medical education and the health care workforce in the United States and Canada. Although RMCs are not new, in the recent years of medical education enrollment expansion, they have seen their numbers increase. Class expansion explains the rapid growth of RMCs in the past 10 years, but it does not adequately describe their function. Often, RMCs have missions that differ from their main campus, especially in the areas of rural and community medicine. The absence of an easy-to-use classification system has led to a lack of current research about RMCs as evidenced by the small number of articles in the current literature. The authors describe the process of the Group on Regional Medical Campuses used to develop attributes of a campus separate from the main campus that constitute a “classification” of a campus as an RMC. The system is broken into four models—basic science, clinical, longitudinal, and combined—and is linked to Liaison Committee on Medical Education standards. It is applicable to all schools and can be applied by any medical school dean or medical education researcher. The classification system paves the way for stakeholders to agree on a denominator of RMCs and conduct future research about their impact on medical education.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.935
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.028
GPT teacher head0.276
Teacher spread0.248 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations0
Published2014
Admission routes1
Has abstractyes

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