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Record W3180076750 · doi:10.1111/codi.15814

Collaboration in colorectal surgical research

2021· article· en· W3180076750 on OpenAlex
Jacob Rosenberg, Eva Angenete, Thomas Pinkney, Aneel Bhangu, Eva Haglind

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueColorectal Disease · 2021
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Surgical Treatments
Canadian institutionsCentre for Global Health Research
Fundersnot available
KeywordsMedicineObservational studyColorectal surgeryClinical researchMedical physicsGeneral surgeryMedical educationSurgeryAbdominal surgeryPathology

Abstract

fetched live from OpenAlex

Surgical research has been under-powered, under-funded and under-delivered for decades. A solution may be to form large research collaborations and thereby enable implementation of successful interventional trials as well as robust international observational studies with thousands of patients. There are many such research collaborations in colorectal surgery, and in this paper we have highlighted the experiences from the West Midlands Research Collaborative (WMRC), the Scandinavian Surgical Outcomes Research Group (SSORG) and the European Society of Coloproctology. With active research networks, it is possible to deliver large, high-quality studies and provide high-level evidence for solving important clinical questions in an efficient and timely manner.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.044
GPT teacher head0.403
Teacher spread0.359 · 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