MétaCan
Menu
Back to cohort
Record W1986688155 · doi:10.1016/s0014-5793(02)02462-6

Excess noise in modified conductance states following the interaction of ryanoids with cardiac ryanodine receptor channels

2002· article· en· W1986688155 on OpenAlexaff
Bhavna Tanna, William H. Welch, Luc Ruest, John L. Sutko, Alan J. Williams

Bibliographic record

VenueFEBS Letters · 2002
Typearticle
Languageen
FieldEngineering
TopicAdvanced Chemical Sensor Technologies
Canadian institutionsUniversité de Sherbrooke
FundersBritish Heart FoundationWellcome Trust
KeywordsRyanodine receptorConductanceBiophysicsNoise (video)ChemistryReceptorPhysicsBiochemistryCondensed matter physicsBiologyComputer science

Abstract

fetched live from OpenAlex

The interaction of ryanodine with the ryanodine receptor (RyR) produces profound changes in channel function. Open probability increases dramatically and conductance is reduced. In this report we describe differences in the properties of reduced conductance states produced by the interaction of ryanodine derivatives with RyR channels. Some reduced conductance states are considerably noisier than the normal open state of the RyR channel. Inspection and analysis of these events reveals that the excess noise arises from transitions between two conductance states. Following the interaction of certain ryanodine derivatives, RyR channels undergo transitions between two conformations with slightly different ion-handling properties.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.145
Threshold uncertainty score0.457

Codex and Gemma teacher scores by category

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

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 head0.015
GPT teacher head0.212
Teacher spread0.197 · 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.

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

Citations5
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueFEBS LettersSame topicAdvanced Chemical Sensor TechnologiesFrench-language works237,207