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Record W1987292901 · doi:10.1034/j.1600-0579.6.s3.20.x

4.4 Electronic management systems

2002· article· en· W1987292901 on OpenAlexaff
Harvey Eplee, Brian Murray, James H. Revere, F Bollmann, G.I. Haddad, J. Klimek, Sergiu Barna, George S. Rhodes, Tuomas Looki, Aiden Malone, Michael P. Molvar, Bob Pienkowski, Meta Schoonheim, Jari‐Pekka Teravainen

Bibliographic record

VenueEuropean Journal Of Dental Education · 2002
Typearticle
Languageen
FieldDentistry
TopicDental Research and COVID-19
Canadian institutionsTrinity College
Fundersnot available
KeywordsConsistency (knowledge bases)Quality (philosophy)CurriculumManagement systemDental educationSoftware deploymentBusinessDental careMedical educationKnowledge managementMedicineMedical emergencyEngineering managementComputer scienceEngineeringOperations managementPsychologyFamily medicinePedagogy

Abstract

fetched live from OpenAlex

The international development and deployment of an electronic modularized dental curriculum is central to the development of an electronic engine to be used for the effective management of dental education. This will ensure continuity in high quality of care across all boundaries, through the continuous updating of its content and linkages to contemporary resources and databases. An electronic engine to be used for the effective management of dental education in a comprehensive dental school/hospital setting is at the core of an international 'virtual' dental education institution. The issue of policy development necessary to ensure consistency, quality and management for an electronic engine is at the very centre of: a) systems management and system databases; b) records of students, patients and personnel; and c) financial records.

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)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.063
Threshold uncertainty score0.211

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0090.006
Open science0.0030.004
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0630.032

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 head0.021
GPT teacher head0.301
Teacher spread0.280 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations2
Published2002
Admission routes1
Has abstractyes

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Same venueEuropean Journal Of Dental EducationSame topicDental Research and COVID-19French-language works237,207