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Record W2332943401 · doi:10.1007/dcr.0b013e3181a0b358

Developing a Research Agenda for The American Society of Colon and Rectal Surgeons

2009· article· en· W2332943401 on OpenAlexaff
Caroline G. Burt, Robert R. Cima, Walter A. Koltun, Charles E. Littlejohn, Rocco Ricciardi, Larissa K. Temple, David A. Rothenberger, Nancy N. Baxter

Bibliographic record

VenueDiseases of the Colon & Rectum · 2009
Typearticle
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsSt. Michael's HospitalUniversity of Toronto
FundersAdvanced Scientific Computing Research
KeywordsMedicineColorectal surgeryDelphi methodColorectal cancerFamily medicineGeneral surgerySurgeryInternal medicineAbdominal surgery

Abstract

fetched live from OpenAlex

PURPOSE: By use of a systematic approach, the aim of this project was to survey a group of colorectal specialists and reach a consensus on the research questions of highest importance in terms of clinical care. METHODS: A modified Delphi process was performed. In Round 1 research questions were solicited from members of The American Society of Colon and Rectal Surgeons. A review group categorized the results, combined similar questions, and presented them to The American Society of Colon and Rectal Surgeons membership in Round 2 for prioritizing according to importance. In Round 3 the 50 questions with the highest scores in Round 2 were reranked by The American Society of Colon and Rectal Surgeons membership to produce the 20 highest-priority research questions. RESULTS: A total of 203 respondents in Round 1 submitted 746 questions. The review team reduced these to 105 individual questions encompassing 21 topics in colorectal surgical practice. In Rounds 2 and 3, 399 and 360 respondents, respectively, prioritized the questions presented. The final 20 items included 14 questions related to colorectal cancer, and 6 were on benign disease topics. CONCLUSIONS: The research agenda produced by this study reflects the clinical issues of greatest importance to colorectal surgeons. The results are of potential benefit to researchers, funding organizations, medical journals, and ultimately, patients.

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 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)0.002
metaresearch head score (Gemma)0.022
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.867
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.273
GPT teacher head0.505
Teacher spread0.232 · 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 teacher head, not a consensus.

Study designObservational
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

Citations36
Published2009
Admission routes1
Has abstractyes

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