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Record W7011320597

Magnetic Resonance and its Applications. Abstracts book. Saint Petersburg State University. April 23-29, 2017

2017· book· en· W7011320597 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueResearch Repository Saint Petersburg State University (Saint Petersburg State University) · 2017
Typebook
Languageen
FieldEnvironmental Science
TopicAdvanced Scientific Techniques and Applications
Canadian institutionsnot available
FundersGebze Teknik ÜniversitesiNatural Sciences and Engineering Research Council of CanadaKazan Federal UniversityBilim, Sanayi ve Teknoloji BakanliğiRussian Science FoundationCentre National de la Recherche ScientifiqueRussian Foundation for Basic ResearchGerman-Russian Interdisciplinary Science Center
KeywordsSaint petersburgSt petersburgState (computer science)Magnetic resonance imagingResonance (particle physics)Electromagnetic radiationObject (grammar)Reputation
DOInot available

Abstract

fetched live from OpenAlex

The International Youth School-Conference “Magnetic resonance and its application” SPINUS-2017 will be held at the St. Petersburg State University in the 14th time. In modern physics, the term “magnetic resonance” refers to a set of phenomena accompanied with the emission or absorption of electromagnetic waves of the radiofrequency diapason by quantum systems (nuclei, electrons, atoms, molecules, etc.). These phenomena, the physical nature of which is of independent interest, provided the basis of radiospectroscopic methods for studying the structure of matter and physico-chemical processes in it. These methods, being contactless, do not destroy an object under a study, that makes them unique and in demand not only in physics and chemistry, but also in medicine, geology, biology, archeology. Now, any medical center with high reputation has a magnetic resonance imaging (MRI).

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.438
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0060.005
Scholarly communication0.0010.003
Open science0.0050.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.001

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 head0.021
GPT teacher head0.248
Teacher spread0.227 · 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