COVID-19 and beyond: a call for action and audacious solidarity to all the citizens and nations, it is humanity’s fight
Bibliographic record
Abstract
<ns5:p> <ns5:bold>Background</ns5:bold> : Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) belongs to a subgroup of coronaviruses rampant in bats for centuries. It caused the coronavirus disease 2019 (COVID-19) pandemic. Most patients recover, but a minority of severe cases experience acute respiratory distress or an inflammatory storm devastating many organs that can lead to patient death. The spread of SARS-CoV-2 was facilitated by the increasing intensity of air travel, urban congestion and human contact during the past decades. Until therapies and vaccines are available, tests for virus exposure, confinement and distancing measures have helped curb the pandemic. </ns5:p> <ns5:p> <ns5:bold>Vision</ns5:bold> : The COVID-19 pandemic calls for safeguards and remediation measures through a systemic response. Self-organizing initiatives by scientists and citizens are developing an advanced collective intelligence response to the coronavirus crisis. Their integration forms Olympiads of Solidarity and Health. Their ability to optimize our response to COVID-19 could serve as a model to trigger a global metamorphosis of our societies with far-reaching consequences for attacking fundamental challenges facing humanity in the 21 <ns5:sup>st</ns5:sup> century. </ns5:p> <ns5:p> <ns5:bold>Mission</ns5:bold> : For COVID-19 and these other challenges, there is no alternative but action. Meeting in Paris in 2003, we set out to "rethink research to understand life and improve health." We have formed an international coalition of academia and industry ecosystems taking a systems medicine approach to understanding COVID-19 by thoroughly characterizing viruses, patients and populations during the pandemic, using openly shared tools. All results will be publicly available with no initial claims for intellectual property rights. This World Alliance for Health and Wellbeing will catalyze the creation of medical and health products such as diagnostic tests, drugs and vaccines that become common goods accessible to all, while seeking further alliances with civil society to bridge with socio-ecological and technological approaches that characterise urban systems, for a collective response to future health emergencies. </ns5:p>
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| 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".