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Record W11132924 · doi:10.3727/096504001108747521

David Wood, Time After Time . Reviewed by

2009· article· en· W11132924 on OpenAlexaff
Robert Piercey

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical Geography and Geographical Thought
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsPhilosophyDeep timeGeologyPaleontology

Abstract

fetched live from OpenAlex

Liver metastasis of primary tumors is clinically a major problem. We examined the antitumor activity of KRN7000, an alpha-galactosylceramide, in mice with liver metastasis of the B16 melanoma. KRN7000 significantly inhibited tumor growth in the liver, and its potency was similar to that of interleukin-12. The KRN7000 administration resulted in a high percentage of cured mice, which acquired tumor-specific immunity. To study what kinds of antitumor effector cells participated in killing tumor cells, we then performed immunohistological analysis of tumor-infiltrating cells, and found that KRN7000 induced marked invasion of NK1.1+ cells, CD8+ cells, and F4/80+ cells (macrophages) into B16 tumor nodules. In addition, it appeared that KRN7000-treated, liver-associated macrophages possessed strong lytic activity against tumor cells. These results suggest that NK cells, NK1.1+ T (NKT) cells, cytotoxic T lymphocytes, and macrophages play an important role in killing tumor cells in the liver, and that KRN7000 may be useful for the treatment of cancer liver metastasis.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.284
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.004

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 head0.005
GPT teacher head0.248
Teacher spread0.243 · 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
GenreOther

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
Published2009
Admission routes1
Has abstractyes

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