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Record W4230796317 · doi:10.3410/f.1018093.207603

Faculty Opinions recommendation of Identification from a combinatorial library of a small molecule that selectively induces apoptosis in cancer cells.

2004· dataset· en· W4230796317 on OpenAlexaff
Dennis G. Hall

Bibliographic record

VenueFaculty Opinions – Post-Publication Peer Review of the Biomedical Literature · 2004
Typedataset
Languageen
FieldChemistry
TopicClick Chemistry and Applications
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsApoptosisCancer cellProgrammed cell deathCancerCell cultureCancer researchChemistrySmall moleculeCell biologyComputational biologyBiologyBiochemistryGenetics

Abstract

fetched live from OpenAlex

The selective induction of death in cancer cells is a major challenge in modern medicine. In this communication we describe the synthesis of an 88-membered combinatorial library, and the subsequent evaluation of these compounds for their ability to selectively induce apoptosis in cancerous cells. A compound was identified from the library that induces apoptosis in U-937 and HL-60 cell lines. This compound is a remarkably selective pro-apoptotic agent for these cancer cell lines, as it does not induce significant death in noncancerous white blood cells, even at concentrations as high as 1000 muM. PMID: 14640619

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.125
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.001
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 head0.035
GPT teacher head0.327
Teacher spread0.291 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2004
Admission routes1
Has abstractyes

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