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Record W1532055256 · doi:10.1109/intmag.2015.7157495

Magnetic nanowires and hyperthermia: How geometry and material affect heat production efficiency

2015· article· en· W1532055256 on OpenAlexaff
María F. Contreras, A. Zaher, Jose E. Perez, Timothy Ravasi, Jürgen Kosel

Bibliographic record

Venue2015 IEEE Magnetics Conference (INTERMAG) · 2015
Typearticle
Languageen
FieldMaterials Science
TopicAnodic Oxide Films and Nanostructures
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMaterials scienceHyperthermiaMagnetic hyperthermiaNanowireSuperparamagnetismMagnetic fieldMagnetic momentMagnetic refrigerationNanostructureNanotechnologyNuclear magnetic resonanceMagnetizationMagnetic nanoparticlesCondensed matter physicsNanoparticleMedicinePhysics

Abstract

fetched live from OpenAlex

Magnetic hyperthermia, which refers to the production of heat by magnetic nanostructures under an alternating magnetic field (AMF), has been previously investigated with superparamagnetic nanobeads as a cancer therapy method. Magnetic nanowires (NWs) used in hyperthermia can be very promising, as it has been shown that they have a larger magnetic moment per unit of volume compared to the nanobeads. Moreover, Fe NWs proved to have a higher heating efficiency compared to Fe nanobeads, when exposed to an AMF at the same concentration [1].

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.020
GPT teacher head0.238
Teacher spread0.218 · 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 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
Published2015
Admission routes1
Has abstractyes

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