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Record W1553033186

Exploiting electromagnetic fields to enhance the delivery of therapeutics to tumors

2015· article· en· W1553033186 on OpenAlexaff
Sylvain Martel

Bibliographic record

VenuePolyPublie (École Polytechnique de Montréal) · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMicro and Nano Robotics
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsSuiteComputer scienceProcess (computing)Electromagnetic fieldSoftwareRisk analysis (engineering)MedicinePhysics
DOInot available

Abstract

fetched live from OpenAlex

Electromagnetic fields can be exploited in various ways to navigate appropriate therapeutic vectors to tumor sites using the most direct vascular routes. Such delivery approach minimizes systemic toxicity that negatively impacts healthy organs and tissues, and results in a larger ratio of therapeutics at the target site that needs treatment. Depending mostly upon the type and the characteristics of the navigable agents being used and the various physiological conditions, different approaches exploiting in various manners the control of electromagnetic fields have been developed by our research group. But due to the difficulty in determining the best method and to help determining which approach would be more appropriated for a particular case, a decision process is proposed here for the first time. Such a model briefly described in this paper could be integrated in a software platform as part of the interventional suite.

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 categoriesnone
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 score0.368
Threshold uncertainty score0.753

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 science0.0010.000
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 head0.013
GPT teacher head0.245
Teacher spread0.232 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2015
Admission routes1
Has abstractyes

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