MétaCan
Menu
Back to cohort
Record W4248048133 · doi:10.1002/9781118633953.ch4

Magnetization, Relaxation, and the Bloch Equation

2014· other· en· W4248048133 on OpenAlexaff
Robert W. Brown, Yu‐Chung N. Cheng, E. Mark Haacke, Michael R. Thompson, Ramesh Venkatesan

Bibliographic record

VenueMagnetic Resonance Imaging · 2014
Typeother
Languageen
FieldChemistry
TopicAdvanced NMR Techniques and Applications
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMagnetizationBloch equationsCondensed matter physicsPrecessionPhysicsLarmor precessionRelaxation (psychology)DipoleSpin (aerodynamics)ProtonProton magnetic momentMagnetic momentMagnetic dipoleMagnetic fieldSpin magnetic momentQuantum mechanics

Abstract

fetched live from OpenAlex

The response of an isolated proton's spin in an external magnetic field has been modeled by the classical Bloch equations of motion of a single magnetic moment. The interactions of the proton spin with its neighboring atoms lead to important modifications to this behavior. The local fields change the spin precession frequency, and the proton can exchange spin energy with the surroundings. This chapter presents the modeling of these effects, as guided by experiment, after introducing the average magnetic dipole moment density (magnetization). It discusses the relaxation of the longitudinal component to M0 and the relaxation of the transverse components to zero.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.006
GPT teacher head0.235
Teacher spread0.229 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations5
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueMagnetic Resonance ImagingSame topicAdvanced NMR Techniques and ApplicationsFrench-language works237,207