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Record W2076265228 · doi:10.1186/s13023-015-0248-3

Defects in fatty acid amide hydrolase 2 in a male with neurologic and psychiatric symptoms

2015· article· en· W2076265228 on OpenAlexafffund
Sandra Sirrs, Clara DM van Karnebeek, Xiaoxue Peng, Casper Shyr, Maja Tarailo‐Graovac, Rupasri Mandal, Daniel Testa, Devin Dubin, Gregory Carbonetti, Steven E. Glynn, Bryan Sayson, Wendy P. Robinson, David S. Wishart, Colin J.D. Ross, Wyeth W. Wasserman, Trevor A. Hurwitz, Graham Sinclair, Martin Kaczocha

Bibliographic record

VenueOrphanet Journal of Rare Diseases · 2015
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversity of British Columbia HospitalSpinal Cord Injury BCPancreas Centre (Canada)British Columbia Centre of Excellence for Women's HealthWorld Wildlife Fund CanadaUniversity of AlbertaChild and Family Research InstituteBC Children's HospitalUniversity of British Columbia
FundersNational Institute on Drug AbuseGenome British ColumbiaMichael Smith Health Research BCChildren's Hospital FoundationNational Institute of General Medical SciencesRadboud UniversiteitCanadian Institutes of Health ResearchGenome Canada
KeywordsMissense mutationFatty acid amide hydrolaseExome sequencingSanger sequencingAtaxiaCompound heterozygosityAutismBiologyMutationMedicineGeneticsPsychiatryGeneCannabinoid receptor

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.012
GPT teacher head0.264
Teacher spread0.252 · 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 designCase report
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

Citations30
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueOrphanet Journal of Rare DiseasesSame topicCannabis and Cannabinoid ResearchFrench-language works237,207