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Record W4385584237 · doi:10.1038/s44276-023-00011-z

Hereditary gastrointestinal polyposis syndromes Rare Disease Collaborative Network consensus statement agreed at the RDCN meeting Birmingham 17th February 2022

2023· letter· en· W4385584237 on OpenAlexfundno aff
Susan K. Clark, Vicky Cuthill, Jackie Hawkins, Warren Hyer, Andy Latchford, Ashish Sinha, Farhat V N Din, Andrew D. Beggs, Anant Desai, Dion Morton, Debbie Hitchen, James Hill, Fiona Lalloo, Katy Newton, Sarah Pugh, Sunil Dolwani, Rachel Hargest, James Horwood, Raji Ramaraj, Mark Rogers, Paul Collins, Frances McNichol, N E Beck, Lucy Side, Frank McDermott

Bibliographic record

VenueBJC Reports · 2023
Typeletter
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsnot available
FundersInstitute of GeneticsMedical Research CouncilUniversity of EdinburghImperial College LondonUniversity Hospital Southampton NHS Foundation TrustCardiff UniversityCentral Manchester University Hospitals NHS Foundation Trust
KeywordsStatement (logic)MedicineGastrointestinal diseaseRare diseaseDiseaseDermatologyInternal medicinePolitical scienceLaw

Abstract

fetched live from OpenAlex

NHS England set out in the Implementation Plan for the UK Strategy for Rare Diseases ( https://www.england.nhs.uk/wp-content/uploads/2018/01/implementation-plan-uk-strategy-for-rare-diseases.pdf ) that it would develop and implement Rare Disease Collaborative Networks (RDCNs), with the definition of a RDCN being a ‘recognised network of member providers, each of which has demonstrable research-active interest in a rare/very rare disease, the aim of the network being to improve patient outcomes’. The network is composed of Rare Disease Collaborative Centres. A Rare Disease Collaborative Centre (RDCC) is a ‘provider that has been recognised as having a demonstrable research-active interest in a rare/very rare disease and who works with other recognised providers in a network to improve patient outcomes’.

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)0.003
metaresearch head score (Gemma)0.023
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.025
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0250.027
Insufficient payload (model declined to judge)0.0130.009

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 head0.025
GPT teacher head0.273
Teacher spread0.249 · 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
GenreOther

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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueBJC ReportsSame topicGenetic factors in colorectal cancerFrench-language works237,207