Cochrane Rehabilitation: 2020 annual report
Bibliographic record
Abstract
During its fourth year of existence, Cochrane Rehabilitation went on to promote evidence-informed health decision-making in rehabilitation. In 2020, the outbreak of the COVID-19 pandemic has made it necessary to alter priorities. In these challenging times, Cochrane Rehabilitation has firstly changed its internal organisation and established a new relevant project in line with pandemic needs: the REH-COVER (Rehabilitation - COVID-19 evidence-based response) action. The aim was to focus on the timely collection, review and dissemination of summarised and synthesised evidence relating to COVID-19 and rehabilitation. Cochrane Rehabilitation REH-COVER action has included in 2020 five main initiatives: 1) rapid living systematic reviews on rehabilitation and COVID-19; 2) interactive living evidence map on rehabilitation and COVID-19; 3) definition of the research topics on "rehabilitation and COVID-19" in collaboration with the World Health Organization (WHO) rehabilitation programme; 4) Cochrane Library special collection on Coronavirus (COVID-19) rehabilitation; and 5) collaboration with COVID-END for the topics "rehabilitation" and "disability." Furthermore, we are still carrying on five different special projects: Be4rehab; RCTRACK; definition of rehabilitation for research purposes; ebook project; and a prioritization exercise for Cochrane Reviews production. The Review Working Area continued to identify and "tag" the rehabilitation-relevant reviews published in the Cochrane library; the Publication Working Area went on to publish Cochrane Corners, working more closely with the Cochrane Review Groups (CRGs) and Cochrane Networks, particularly with Cochrane Musculoskeletal, Oral, Skin and Sensory Network; the Education Working Area, the most damaged in 2020, tried to continue performing educational activities such as workshops in different online meetings; the Methodology Working Area organized the third and fourth Cochrane Rehabilitation Methodological (CRM) meetings respectively in Milan and Orlando; the Communication Working Area spread rehabilitation evidences through different channels and translated the contents in different languages.
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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 | 0.052 | 0.103 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.035 | 0.021 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.023 | 0.014 |
| Open science | 0.007 | 0.012 |
| Research integrity | 0.012 | 0.010 |
| Insufficient payload (model declined to judge) | 0.129 | 0.100 |
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".