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Record W2096089717 · doi:10.1002/anie.201302374

Opsin, a Structural Model for Olfactory Receptors?

2013· article· en· W2096089717 on OpenAlexaff
Jung Hee Park, Takefumi Morizumi, Yafang Li, Joo Eun Hong, E.F. Pai, Klaus Peter Hofmann, Hui‐Woog Choe, Oliver P. Ernst

Bibliographic record

VenueAngewandte Chemie International Edition · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicReceptor Mechanisms and Signaling
Canadian institutionsPrincess Margaret Cancer CentreOntario Institute for Cancer ResearchUniversity of Toronto
Fundersnot available
KeywordsG protein-coupled receptorOpsinReceptorComputational biologyComputer scienceOlfactory receptorRhodopsinOlfactory systemNeuroscienceWorld Wide WebCognitive scienceInformation retrievalBiologyPsychologyGeneticsBiochemistry

Abstract

fetched live from OpenAlex

Receptor-ligand interaction: Olfactory receptors (ORs) are G-protein-coupled receptors (GPCRs), which detect signaling molecules such as hormones and odorants. The structure of opsin, the GPCR employed in vision, with a detergent molecule bound deep in its orthosteric ligand-binding pocket provides a template for OR homology modeling, thus enabling investigation of the structural basis of the mechanism of odorant-receptor recognition.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.002

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 head0.021
GPT teacher head0.258
Teacher spread0.237 · 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 designTheoretical or conceptual
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

Citations70
Published2013
Admission routes1
Has abstractyes

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