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Record W2911072167 · doi:10.1136/jclinpath-2018-205672

Neurotrophic tropomyosin or tyrosine receptor kinase (NTRK) genes

2019· review· en· W2911072167 on OpenAlexaff
Runjan Chetty

Bibliographic record

VenueJournal of Clinical Pathology · 2019
Typereview
Languageen
FieldMedicine
TopicHER2/EGFR in Cancer Research
Canadian institutionsToronto General HospitalUniversity Health Network
FundersMemorial Sloan-Kettering Cancer Center
KeywordsTropomyosinBiologyTropomyosin receptor kinase BTyrosine kinaseGeneFusion geneNeurotrophinCancer researchImmunohistochemistryFusion proteinReceptor tyrosine kinaseTropomyosin receptor kinase CTrk receptorCell biologyReceptorKinaseNeurotrophic factorsImmunologyActinSignal transductionGeneticsPlatelet-derived growth factor receptor

Abstract

fetched live from OpenAlex

The neurotrophic tropomyosin or tyrosine receptor kinase (NTRK) genes (1-3) are proto-oncogenes that when activated are encountered in a wide array of tumours. The recent advent of very specific and selective inhibitors of their gene fusions makes the NRTK gene fusions actionable. NRTK gene fusions are very characteristic of specific tumours: salivary mammary analogue secretory carcinoma, breast secretory carcinoma, infantile fibrosarcoma and congenital mesoblastic nephroma. Over 90% of these tumours bear NTRK gene fusions. While next-generation sequencing is the current platform of choice for the detection of NTRK fusions, immunohistochemistry also shows great promise. Immunohistochemical localisation of the fusion protein to the nucleus, cytoplasm, nuclear membrane and cell membrane is indicative of specific gene fusions involving the NTRK genes.

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)0.005
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.951
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0080.003
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0020.001

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 head0.481
GPT teacher head0.590
Teacher spread0.109 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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

Citations31
Published2019
Admission routes1
Has abstractyes

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