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Record W2319762102 · doi:10.1155/2001/159021

The Changing Medical Research Scene

2001· article· en· W2319762102 on OpenAlexaffabout
Louis‐Philippe Boulet

Bibliographic record

VenueCanadian Respiratory Journal · 2001
Typearticle
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsCanadian Thoracic Society
Fundersnot available
KeywordsMedicineMEDLINEMedical physicsData science

Abstract

fetched live from OpenAlex

Although the basic principles of medical research have not changed much over the past century, the ways that research is conducted has changed significantly, particularly over the past two decades. One aspect that has changed a great deal is the composition of research teams. In the past, researchers were working in isolation or in small groups, while today, multiple partnerships and large groups have become the rule. Furthermore, methods have progressed markedly, high technology is omnipresent and communications have achieved an unprecedented speed. The number of research works published has increased exponentially. This has created a strain for researchers having to balance the requirement for specialization with the need to cross discipline boundaries in research. Mondialization has rapidly reached the medical scene, and research in particular. Collaboration between groups of researchers from different universities, within Canada and from other countries, has allowed fruitful exchanges of expertise, and national and/or international institutions or organizations have facilitated the networking of research groups. Also, efforts are being made to have scientists from different domains work together, and although there may be difficulties in regard to their respective “specialized culture or technical language”, these collaborations may lead to new ways of approaching difficult problems and innovative ways of investigating or treating them. Not only have collaborations between different academic milieux been fruitful but, increasingly, joint university-industry initiatives have flourished. New modes of linking researchers and caregivers have been developed, particularly to help identify specific research targets and to develop ways to translate findings into patient care, adding further dimensions to the research process. It is in this context that the recently formed Institute of Circulatory and Respiratory Health (ICRH), part of the Canadian Institutes of Health Research, has initiated its activities. The Institute aims to support research into the causes, prevention, screening, diagnosis, treatment support systems and palliation for a wide range of conditions affecting the heart, lung, brain, blood and blood vessels. This research will be done in partnership with other organizations, such as the Canadian Lung Association and the Canadian Thoracic Society. However, the nature of this partnership may take different forms, including joint support to the following: investigator-generated research (operating grants) and projects related to targeted ‘priority’ areas of research; regionally based training centres providing an infrastructure and mentorship to support the training of fellows and/or graduate students; fellowships in the respiratory field; multicentre networks working on a common theme (group grants); and interinstitute initiatives. Announcements of various programs have already been made, with more to come, and discussions with provincial lung associations should lead to a definition of the terms of agreement for these joint ICRH-Canadian Lung Association/Canadian Thoracic Society programs. You can check those developments on the Canadian Institutes of Health Research Web site (www.cihr.ca).

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)0.049
metaresearch head score (Gemma)0.061
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.972
Threshold uncertainty score0.258

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0490.061
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0060.005
Science and technology studies0.0150.030
Scholarly communication0.0250.020
Open science0.0040.015
Research integrity0.0220.031
Insufficient payload (model declined to judge)0.0230.006

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 head0.275
GPT teacher head0.484
Teacher spread0.210 · 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.

Study designNot applicable
DomainEvaluation
GenreCommentary

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

Citations1
Published2001
Admission routes2
Has abstractyes

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