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Record W2064118802 · doi:10.1080/03008200290001212

Krox-26 is a Novel C 2 H 2 Zinc Finger Transcription Factor Expressed in Developing Dental and Osteogenic Tissues

2002· article· en· W2064118802 on OpenAlexafffund
Bernhard Ganss, William Teo, Honghong Chen, Tiffany Poon

Bibliographic record

VenueConnective Tissue Research · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topicdental development and anomalies
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsZinc fingerZinc finger transcription factorTranscription factorBiologyCraniofacialCell biologyTranscription (linguistics)GeneLIM domainGenetics

Abstract

fetched live from OpenAlex

The development of teeth through epithelial-mesenchymal interactions is mediated on a molecular level by a network of secreted growth factors and responsive transcription factors. Although zinc finger transcription factors constitute by far the largest class of transcriptional regulators with an estimated number of approximately 1000 genes present in mammals [14], little is known about their role in the regulation of mineralized tissue formation. A fragment (Y150) of the novel C2H2 zinc finger transcription factor Krox-26 has initially been isolated from highly proliferative dental pulp tissue in rats [19]. The objective of this study was to clone the full-length cDNA sequence of the murine homologue and to determine its mRNA and protein expression pattern during mouse embryonic development. Mouse Krox-26 contains five C2H2 zinc finger repeats. Its expression was found to be most prominent in the developing craniofacial bones and dental organs. These results suggest Krox-26 as a potential regulator of gene transcription during the development of teeth and the craniofacial skeleton.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.001

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 head0.084
GPT teacher head0.344
Teacher spread0.260 · 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 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

Citations15
Published2002
Admission routes2
Has abstractyes

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