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Record W2122310551 · doi:10.1158/0008-5472.can-05-3450

Identifying Cancer Stem Cells in Solid Tumors: Case Not Proven

2006· letter· en· W2122310551 on OpenAlexaff
Rićhard P. Hill

Bibliographic record

VenueCancer Research · 2006
Typeletter
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health NetworkUniversity of TorontoOntario Institute for Cancer Research
Fundersnot available
KeywordsCancer stem cellCancerLeukemiaStem cellCancer researchCancer cellSolid tumorIdentification (biology)BiologyPathologyMedicineImmunologyGenetics

Abstract

fetched live from OpenAlex

Building on studies of leukemia, a number of recent articles have reported data suggesting that cancer stem cells could be isolated from solid human cancers. Some of these reports have speculated that the isolation of these cells will allow the identification of the specific molecular properties that can be targeted for therapeutic purposes. Although previous work with animal model systems also suggests the presence of stem cells in solid tumors, there remain many uncertainties, both theoretical and technical, about the interpretation of the current results. The case that a small proportion of cells in solid tumors are specific cancer stem cells and that these cells can be successfully identified and isolated has not yet been proven.

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)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.029
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0020.005
Open science0.0020.001
Research integrity0.0290.013
Insufficient payload (model declined to judge)0.0030.003

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 head0.186
GPT teacher head0.452
Teacher spread0.266 · 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 designNot applicable
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

Citations246
Published2006
Admission routes1
Has abstractyes

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