MétaCan
Menu
Back to cohort
Record W7132104419

RMN du xénon absorbé utilisé comme sonde pour l’étude de solides micro- et mésoporeux, polymères, cristaux liquides, solutions, flammes, protéines et pour l’imagerie

2005· article· en· W7132104419 on OpenAlexvenueno aff
Kristin Bartik, Philippe Choquet, André Constantinesco, Guillaume Duhamel, J. Fraissard, Jean‐Noël Hyacinthe, Jukka Jokisaari, Emanuela Locci, Thomas J. Lowery, Michel Luhmer, Thomas Meersmann, Igor L. Moudrakovski, Galina E. Pavlovskaya, Kimberly L. Pierce, Alexander Pines, John A. Ripmeester, Ville‐Veikko Telkki, W. S. Veeman

Bibliographic record

VenueNPARC · 2005
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNMR spectroscopy and applications
Canadian institutionsnot available
Fundersnot available
KeywordsPorosityAmorphous solidMesoporous materialXenonCombustionCharacterization (materials science)Solid-state
DOInot available

Abstract

fetched live from OpenAlex

We present in this paper some examples of the applications of the Nuclear Magnetic Resonance (NMR) of xenon used as a probe in the study of different chemical environments : determination of the porosity of micro- and mesoporous solids, evaluation of the concentrations and sizes of amorphous domains in solid polymers, characterization of liquid crystals, study of combustion processes at high temperature, determination of the structure and dynamics of organic systems and proteins in solution, assessment of cerebral blood flow.

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)0.001
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.025
GPT teacher head0.339
Teacher spread0.314 · 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

Citations0
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueNPARCSame topicNMR spectroscopy and applicationsFrench-language works237,207