Standards for conducting and reporting consensus and recommendation documents: European Society of Cardiovascular Radiology policy from the Guidelines Committee
Bibliographic record
Abstract
Cardiovascular imaging is exponentially increasing in the diagnosis, risk stratification, and therapeutic management of patients with cardiovascular disease. The European Society of Cardiovascular Radiology (ESCR) is a non-profit scientific medical society dedicated to promoting and coordinating activities in cardiovascular imaging. The purpose of this paper, written by ESCR committees and Executive board members and approved by the ESCR Executive Board and Guidelines committee, is to codify a standardized approach to creating ESCR scientific documents. Indeed, consensus development methods must be adopted to ensure transparent decision-making that optimizes national and global health and reaches a certain scientific credibility. ESCR consensus documents developed based on a rigorous methodology will improve their scientific impact on the management of patients with cardiac involvement. CRITICAL RELEVANCE STATEMENT: This document aims to codify the methodology for producing consensus documents of the ESCR. These ESCR indications will broaden the scientific quality and credibility of further publications and, consequently, the impact on the diagnostic management of patients with cardiac involvement. KEY POINTS: Cardiovascular imaging is exponentially increasing for diagnosis, risk stratification, and therapeutic management. The ESCR is committed to promoting cardiovascular imaging. A rigorous methodology for ESCR consensus documents will improve their scientific impact.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".