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Record W1989312956 · doi:10.1155/2010/816595

Involvement of Aberrant Glycosylation in Thyroid Cancer

2010· article· en· W1989312956 on OpenAlexfundno aff
Eiji Miyoshi, Yasuhiro Ito, Yoko Miyoshi

Bibliographic record

VenueJournal of Oncology · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGlycosylation and Glycoproteins Research
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsGlycomicsGlycosylationCarcinogenesisThyroid cancerPathologicalThyroidGlycanCancerCancer researchMedicineComputational biologyOligosaccharideFunction (biology)GlycosyltransferaseBioinformaticsGlycoproteinBiologyPathologyBiochemistryCell biologyInternal medicineEnzyme

Abstract

fetched live from OpenAlex

Glycosylation is one of the most common posttranslational modification reactions and nearly half of all known proteins in eukaryotes are glycosylated. In fact, changes in oligosaccharides structures are associated with many physiological and pathological events, including cell growth, migration and differentiation, and tumor invasion. Therefore, functional glycomics, which is a comprehensive study of the structures and functions of glycans, is attracting the increasing attention of scientists in various fields of life science. In cases of thyroid cancer, the biological characters and prognosis are completely different in each type of histopathology, and their oligosaccharide structures as well as the expression of glycosyltransferases are also different. In this review, we summarized our previous papers on oligosaccharides and thyroid cancers and discussed a possible function of oligosaccharides in the carcinogenesis in thyroid cancer.

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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.345
Teacher spread0.325 · 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

Citations38
Published2010
Admission routes1
Has abstractyes

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