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Record W2125601604 · doi:10.1177/0022034513508557

Integrating Research into Dental Student Training

2013· editorial· en· W2125601604 on OpenAlexaboutno aff
Joshua J. Emrick, Angela Gullard

Bibliographic record

VenueJournal of Dental Research · 2013
Typeeditorial
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsnot available
FundersNational Institute of Dental and Craniofacial ResearchInternational Association for Dental Research
KeywordsAccreditationCurriculumDental researchMedical educationAttendanceEvidence-based dentistryMedicineDental educationPsychologyPolitical scienceDentistryPedagogyAlternative medicine

Abstract

fetched live from OpenAlex

The integration of research into dental education is necessary to ensure that evidence-based practice reaches the clinical setting and that dentistry remains a scientifically driven health profession. Consequently, dental accreditation standards in the United States and Canada require dental schools to integrate research components into curricula. Organizations (e.g., NIDCR, ADEA, AADR, IADR, and NSRG) provide some opportunities for dental students to experience research. Assessment of the integration of research into dental curricula suggests that US students are interested in learning and utilizing evidence-based practice, but lack adequate time for research participation. Records show limited student involvement in research organizations internationally (i.e., AADR and IADR). Vague accreditation standards and limited research opportunities outside of dental schools may be barriers. We lack an understanding of the status of integration of research into dental curricula internationally, but predict that similar issues exist. We propose that dental institutions consider implementing the following: (1) curriculum components to assess the use of evidence-based practice, (2) faculty and student seminars for discussing evidence-based practice, (3) subsidization of student membership in dental research organizations (e.g., AADR and IADR), and (4) sponsorship of students as institutional representatives at annual research meetings (e.g., IADR, AADR, ADA, and ADEA meetings), with subsequent school-wide dissemination of knowledge attained from attendance.

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)0.061
metaresearch head score (Gemma)0.349
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.288
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0610.349
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0020.029
Insufficient payload (model declined to judge)0.0010.001

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 head0.401
GPT teacher head0.635
Teacher spread0.234 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEditorial

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

Citations37
Published2013
Admission routes1
Has abstractyes

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