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Record W2097155260 · doi:10.4161/cbt.7.7.6492

The art of killing: double stroke with apoptin and survivin as a novel approach in cancer therapy

2008· letter· en· W2097155260 on OpenAlexaff
Soumya Panigrahi, Thomas Klonisch, Marek Łoś

Bibliographic record

VenueCancer Biology & Therapy · 2008
Typeletter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell death mechanisms and regulation
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsSurvivinGene knockdownCancer researchMedicineCancerApoptosisCancer cellOncologyInternal medicineBiologyGenetics

Abstract

fetched live from OpenAlex

Commentary to:Survivin knockdown combined with apoptin overexpression inhibits cell growth significantlyQin Liu, Hanjiang Fu, Ruiyun Xing, Yi Tie, Jie Zhu, Zhixian Sun, Xiaofei Zheng

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)0.003
metaresearch head score (Gemma)0.010
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: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.038
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0030.003
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0380.043
Insufficient payload (model declined to judge)0.0040.004

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 head0.031
GPT teacher head0.277
Teacher spread0.246 · 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
GenreCommentary

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

Citations8
Published2008
Admission routes1
Has abstractyes

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