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Thermal Conductivity of<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:msub><mml:mi>Ho</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:msub><mml:mi>Ti</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:msub><mml:mi mathvariant="bold">O</mml:mi><mml:mn>7</mml:mn></mml:msub></mml:math>along the [111] Direction

2013· article· lv· W2396818042 on OpenAlexaff
W. H. Toews, Songtian S. Zhang, K. A. Ross, H. A. Dabkowska, B. D. Gaulin, R. W. Hill

Bibliographic record

VenuePhysical Review Letters · 2013
Typearticle
Languagelv
FieldPhysics and Astronomy
TopicAdvanced Condensed Matter Physics
Canadian institutionsCanadian Institute for Advanced ResearchBrockhouse Institute for Materials ResearchMcMaster UniversityUniversity of Waterloo
Fundersnot available
KeywordsThermal conductivityDebye modelCondensed matter physicsMagnetic fieldPhysicsField (mathematics)DebyeMaterials sciencePhononThermodynamicsQuantum mechanics

Abstract

fetched live from OpenAlex

Thermal transport measurements have been made on the spin-ice material Ho(2)Ti(2)O(7) in an applied magnetic field with both the heat current and the field parallel to the [111] direction for temperatures from 50 mK to 1.2 K. A large magnetic field >6 T is applied to suppress the magnetic contribution to the thermal conductivity in order to extract the lattice conductivity. The low field thermal conductivity thus reveals a magnetic field dependent contribution to the conductivity which both transfers heat and scatters phonons. We interpret these magnetic excitations as monopolelike excitations and describe their behavior via existing Debye-Hückel theory.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.914
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0030.005
Meta-epidemiology (broad)0.0020.006
Bibliometrics0.0010.003
Science and technology studies0.0040.004
Scholarly communication0.0030.005
Open science0.0050.004
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.2140.007

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 head0.017
GPT teacher head0.250
Teacher spread0.233 · 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; both teacher heads agree on what is shown here.

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

Citations23
Published2013
Admission routes1
Has abstractyes

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