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Record W2063847092 · doi:10.5582/ddt.2011.v5.3.107

Prospects of cancer biotherapy

2011· article· en· W2063847092 on OpenAlexaff
Xishan Hao

Bibliographic record

VenueDrug Discoveries & Therapeutics · 2011
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsPhenomenome Discoveries (Canada)
Fundersnot available
KeywordsRadiation therapyMedicineImmune systemCancer researchCancerTargeted therapyCancer cellImmunotherapyCancer treatmentGenetic enhancementChemotherapyImmunologyOncologyInternal medicineBiologyGene

Abstract

fetched live from OpenAlex

Biotherapy became recognized as the fourth modality of cancer treatment applied after surgical treatment, radiotherapy and chemotherapy since the Biological Response Modifier (BRM) theory was proposed by Dr. Oldham in the 1980s (1). Cancer biotherapy is a therapeutic method that could prohibit the growth of tumors through mobilizing the host's immune system or via the effect of biological agents, thereby regulating the body's biological responses (2). Biotherapy is regarded as the most vigorous and promising strategy among the cancer multimodality treatments in this century due to its advantages of high safety and effectiveness as well as low side-effects (2-4). Treatment methods of biotherapy are emerging with the development of such subjects as immunology, cell biology and molecular biology. Currently, the main approaches of biotherapy include molecule targeted therapy, gene therapy and cell therapy. ...

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.182
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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 head0.056
GPT teacher head0.340
Teacher spread0.284 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations3
Published2011
Admission routes1
Has abstractyes

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