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Ripmeester, John A.: Forty-Plus Years of Research in Solid-State NMR Spectroscopy

2010· reference-entry· en· W1481519497 on OpenAlexaffabout
John A. Ripmeester

Bibliographic record

VenueEncyclopedia of Magnetic Resonance · 2010
Typereference-entry
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsSupramolecular chemistryAsset (computer security)Clathrate hydrateSolid-state nuclear magnetic resonanceChemistryNuclear magnetic resonance spectroscopyCharacterization (materials science)Materials scienceNanotechnologyHydrateCrystallographyOrganic chemistryComputer sciencePhysicsCrystal structureNuclear magnetic resonance

Abstract

fetched live from OpenAlex

As in the case of most researchers, I spent the early part of my career in learning the fundamentals—in this case, solid-state NMR as practiced in the late 1960s and early 1970s. This background eventually gave me employment at the National Research Council of Canada where my expertise was seen as a valuable asset to venture into detailed studies of dynamics in clathrate hydrates. This led to the exploration of new approaches, e.g., the exploration of 129Xe NMR spectroscopy for the characterization of pore space as well as the exploration of new materials—generally classifiable as guest–host and supramolecular solids. The research group which I led for a number of years, with expanded expertise in NMR and complementary techniques, became known for the ability to characterize complex materials where disorder and dynamics were a problem. With the recent global interest in natural gas hydrates, my interests have swung back to concentrating on understanding structures and processes in this challenging class of labile minerals.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.779
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.018
GPT teacher head0.291
Teacher spread0.274 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2010
Admission routes2
Has abstractyes

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