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Record W2760375760 · doi:10.1039/c7sm01145h

Tunable hydrodynamics: a field-frequency phase diagram of a non-equilibrium order-to-disorder transition

2017· article· en· W2760375760 on OpenAlexafffund
Somayeh Khajehpour Tadavani, Anand Yethiraj

Bibliographic record

VenueSoft Matter · 2017
Typearticle
Languageen
FieldMaterials Science
TopicMaterial Dynamics and Properties
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhase diagramOrder (exchange)Field (mathematics)Phase transitionDiagramStatistical physicsPhysicsCondensed matter physicsPhase (matter)Materials scienceThermodynamicsMathematicsQuantum mechanicsEconomicsStatistics

Abstract

fetched live from OpenAlex

Correction for 'Tunable hydrodynamics: a field-frequency phase diagram of a non-equilibrium order-to-disorder transition' by Somayeh Khajehpour Tadavani et al., Soft Matter, 2017, 13, 7412-7424.

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)0.001
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.003
Open science0.0020.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0100.002

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 head0.008
GPT teacher head0.259
Teacher spread0.251 · 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
Published2017
Admission routes2
Has abstractyes

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