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Record W1986703876 · doi:10.1111/adj.12131

The genesis of craniofacial biology as a health science discipline

2014· article· en· W1986703876 on OpenAlexaff
GH Sperber, SM Sperber

Bibliographic record

VenueAustralian Dental Journal · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topicdental development and anomalies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCraniofacialPhysiologyBiologyDentistryAnatomyNeuroscienceMedicineGenetics

Abstract

fetched live from OpenAlex

The craniofacial complex encapsulates the brain and contains the organs for key functions of the body, including sight, hearing and balance, smell, taste, respiration and mastication. All these systems are intimately integrated within the head. The combination of these diverse systems into a new field was dictated by the dental profession's desire for a research branch of basic science devoted and attuned to its specific needs. The traditional subjects of genetics, embryology, anatomy, physiology, biochemistry, dental materials, odontology, molecular biology and palaeoanthropology pertaining to dentistry have been drawn together by many newly emerging technologies. These new technologies include gene sequencing, CAT scanning, MRI imaging, laser scanning, image analysis, ultrasonography, spectroscopy and visualosonics. A vibrant unitary discipline of investigation, craniofacial biology, has emerged that builds on the original concept of 'oral biology' that began in the 1960s. This paper reviews some of the developments that have led to the genesis of craniofacial biology as a fully-fledged health science discipline of significance in the advancement of clinical dental practice. Some of the key figures and milestones in craniofacial biology are identified.

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)0.004
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.998
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0020.022
Scholarly communication0.0050.004
Open science0.0010.003
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0030.001

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 head0.012
GPT teacher head0.313
Teacher spread0.302 · 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.

Study designTheoretical or conceptual
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

Citations2
Published2014
Admission routes1
Has abstractyes

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