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Review of Outcomes from a Change in Faculty Clinic Management in a U.S. Dental School

2010· article· en· W4237588462 on OpenAlexaff
Nader Nadershahi, Eric S. Salmon, Nava Fathi, Karl Schmedders, Jace Hargıs

Bibliographic record

VenueJournal of Dental Education · 2010
Typearticle
Languageen
FieldHealth Professions
TopicDental Education, Practice, Research
Canadian institutionsKellogg's (Canada)
Fundersnot available
KeywordsDenturesDental educationMedicineDental clinicGeneralist and specialist speciesDental careVariety (cybernetics)Family medicineMedical educationDentistryPsychology

Abstract

fetched live from OpenAlex

Dental schools use a variety of clinic management models with the goals of promoting patient care, student education, and fiscal responsibility. In 2004, the University of the Pacific Arthur A. Dugoni School of Dentistry transitioned to a more generalist model with these goals in mind. The purpose of this study was to evaluate the outcomes of this clinic model change relative to the quantity of specific procedures completed by students. The quantity of procedures completed by each student from the classes of 1995 through 2009 were compiled from our electronic clinic management system and analyzed. The post‐transition group (2004–09) showed a greater number of completed oral diagnosis and treatment planning and root planing procedures per student compared to the pre‐transition group (1995–2003), but fewer crowns, root canals, operative procedures, and dentures. Because the higher procedure numbers were for low‐cost procedures, our transition to a generalist model did not necessarily enhance clinic income but may support student learning and enhanced patient care.

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)0.006
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.032
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.009
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.170
GPT teacher head0.592
Teacher spread0.422 · 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 designObservational
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

Citations5
Published2010
Admission routes1
Has abstractyes

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