ICONE: An International Consortium of Neuro Endovascular Centres
Bibliographic record
Abstract
SUMMARY: The proliferation of new endovascular devices and therapeutic strategies calls for a prudentand rational evaluation of their clinical benefit. This evaluation must be done in an effective manner and in collaboration with industry. Such research initiative requires organisation a land methodological support to survive and thrive in a competitive environment. We propose the formation of an international consortium, an academic alliance committed to the pursuit of effective neurovascular therapies. Such a consortium would be dedicated to the designand execution of basic science, device developmentand clinical trials. The Consortium is owned and operated by its members. Members are international leaders in neurointerventional research and clinical practice. The Consortium brings competency, knowledge, and expertise to industry as well as to its membership across aspectrum of research initiatives such as: expedited review of clinical trials, protocol development, surveys and systematic reviews; laboratory expertise and support for research design and grant applications to public agencies. Once objectives and protocols are approved, the Consortium provides a stable network of centers capable of timely realization of clinical trials or pre clinical investigations in an optimal environment. The Consortium is a non-profit organization. The potential revenue generated from clientsponsored financial agreements will be redirected to the academic and research objectives of the organization. The Consortium wishes to work inconcert with industry, to support emerging trends in neurovascular therapeutic development. The Consortium is a realistic endeavour optimally structured to promote excellence through scientific appraisal of our treatments, and to accelerate technical progress while maximizing patients' safety and welfare.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.048 | 0.015 |
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 source (direct Gemma or distilled Codex), 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".