MétaCan
Menu
Back to cohort
Record W2121105777 · doi:10.1124/pr.59.1.5

International Union of Basic and Clinical Pharmacology. LXVII. Recommendations for the Recognition and Nomenclature of G Protein-Coupled Receptor Heteromultimers

2007· review· en· W2121105777 on OpenAlexaff
Jean‐Philippe Pin, Richard R. Neubig, Michel Bouvier, Lakshmi A. Devi, Marta Filizola, Jonathan A. Javitch, Martin J. Lohse, Graeme Milligan, Krzysztof Palczewski, Marc Parmentier, Michael Spedding

Bibliographic record

VenuePharmacological Reviews · 2007
Typereview
Languageen
FieldNursing
TopicBiochemical Analysis and Sensing Techniques
Canadian institutionsInstitute for Research in Immunology and CancerUniversité de Montréal
FundersNational Institute on Drug Abuse
KeywordsG protein-coupled receptorNomenclatureReceptorBiologyComputational biologyHeterologous expressionObligateNeuroscienceCell biologyBiochemistryGeneTaxonomy (biology)Recombinant DNA

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.015
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0030.005
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0150.031

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 head0.285
GPT teacher head0.491
Teacher spread0.206 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations272
Published2007
Admission routes1
Has abstractno

Explore more

Same venuePharmacological ReviewsSame topicBiochemical Analysis and Sensing TechniquesFrench-language works237,207