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Record W3045970153 · doi:10.1111/jre.12787

How Tony Melcher advanced our understanding of periodontal biology and regeneration

2020· article· en· W3045970153 on OpenAlexaffabout
D. M. Brunette, Richard P. Ellen, Christopher A. McCulloch

Bibliographic record

VenueJournal of Periodontal Research · 2020
Typearticle
Languageen
FieldMedicine
TopicPeriodontal Regeneration and Treatments
Canadian institutionsUniversity of TorontoUniversity of British Columbia
Fundersnot available
KeywordsPeriodontiumDisciplineDental researchEngineering ethicsExperimental biologySociologyPolitical scienceMedicineDentistrySocial scienceBiologyEngineering

Abstract

fetched live from OpenAlex

Tony Melcher, a highly influential and forward-thinking scientist and teacher, focussed on the origins, behaviour and regulation of cells in periodontal tissues. His recent death in April 2020, has motivated us to highlight his multi-level contributions to research in biology and the dental sciences. Tony was particularly adept at recognizing the inherent instructive power of the periodontium, most notably as a model system for studying the inter-relationships between the structure, development and functions of connective tissues. Further, his mentoring of dozens of students who subsequently went on to develop their own careers in research, and his leadership in promoting collaborations in dental sciences world-wide, engendered important advances in the importance and utility of research relating to oral tissues. Here, we reflect upon his development of a large, multi-disciplinary research enterprise, the MRC Group in Periodontal Physiology at the University of Toronto and brief commentaries of those who worked with him there. We examine his early career development and then go on to consider some of his most highly cited publications and their impact on subsequent research trends.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.324
Threshold uncertainty score0.497

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.228
GPT teacher head0.430
Teacher spread0.202 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2020
Admission routes2
Has abstractyes

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