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Record W2603412331 · doi:10.4155/tde-2016-0088

Targeting Active Cancer Cells With Smart Bullets

2017· review· en· W2603412331 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTherapeutic Delivery · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Research and Treatments
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsCancerBusinessNanotechnologyMedicineMaterials scienceInternal medicine

Abstract

fetched live from OpenAlex

Paul Ehrlich's 'magic bullet' concept has stimulated research for therapeutic agents with the capability to go straight to their intended targets. The 'magic bullet' concept is still considered the ultimate approach to maximize the therapeutic effects of a given therapeutic agent without affecting nontargeted tissues. But so far, there has never been a therapeutic agent or a delivery system that goes straight to the target in the body, and no approach has provided anything better than just a few percents of the total administered dose reaching the intended target sites. But engineering principles can transform systematically circulating vectors that so far were based primarily on physical characteristics and biochemical principles alone, as smart therapeutic agents with the required propulsion-navigation-homing capabilities to enable them to go straight to their intended targets.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.996
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.076
GPT teacher head0.379
Teacher spread0.304 · 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