MétaCan
Menu
Back to cohort
Record W2066877940 · doi:10.1309/ajcpgxk0fr4mhihb

Nectin 4 Overexpression in Ovarian Cancer Tissues and Serum

2010· article· en· W2066877940 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Journal of Clinical Pathology · 2010
Typearticle
Languageen
FieldImmunology and Microbiology
TopicGalectins and Cancer Biology
Canadian institutionsBC Cancer Agency
FundersNational Cancer Institute
KeywordsOvarian cancerImmunohistochemistryCancerReverse transcriptaseBiomarkerBiologyPathologyNectinFlow cytometryOvaryCancer researchPolymerase chain reactionMedicineCellInternal medicineMolecular biologyEndocrinologyGeneCell adhesion

Abstract

fetched live from OpenAlex

Early detection of ovarian cancer is difficult owing to the lack of specific and sensitive tests available. Previously, we found expression of nectin 4 to be increased in ovarian cancer compared with normal ovaries. Reverse transcriptase-polymerase chain reaction (RT-PCR) and quantitative RT-PCR validated the overexpression of nectin 4 messenger RNA in ovarian cancer compared with normal ovarian cell lines and tissues. Protein levels of nectin 4 were elevated in ovarian cancer cell lines and tissue compared with normal ovarian cell lines as demonstrated by Western immunoblotting, flow cytometry, and immunohistochemical staining of tissue microarray slides. Cleaved nectin 4 was detectable in a number of patient serum samples by enzyme-linked immunosorbent assay. In patients with benign gynecologic diseases with high serum CA125 levels, nectin 4 was not detected in the majority of cases, suggesting that nectin 4 may serve as a potential biomarker that helps discriminate benign gynecologic diseases from ovarian cancer in a panel with CA125.

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.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.444
Threshold uncertainty score0.630

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.375
Teacher spread0.354 · 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