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Record W3094545331 · doi:10.1213/ane.0000000000005061

In Response

2020· letter· en· W3094545331 on OpenAlexaffabout
C Bong, Christopher Brasher, Edson Chikumba, Robert McDougall, Jannicke Mellin‐Olsen, Angela Enright

Bibliographic record

VenueAnesthesia & Analgesia · 2020
Typeletter
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsRoyal Jubilee HospitalUniversity of British Columbia
Fundersnot available
KeywordsPsychology

Abstract

fetched live from OpenAlex

Thank you for the opportunity to respond to the letter by Dr Subedi1 wherein he has raised some very important points about managing the coronavirus disease 2019 (COVID-19) pandemic when working in a low-resource environment. It seems that Nepal has been very effective in coping with the pandemic thus far. Nevertheless, as in other countries, there are huge stresses placed on all health care workers (HCWs), both physically and mentally. As he says, governments need to recognize them for their commitment and loyalty to their patients. Certainly, the general populations in many countries have done so as evidenced by the singing (Italy), playing of musical instruments (Spain), and even banging of pots and pans (United States and Canada). But HCW, and others maintaining systems during the crisis, need more than that. He outlines some of the important things, such as proper sleep, food, and connections with loved ones. We could add others such as peer support and professional support when necessary. National and international anesthesia societies have also addressed this issue2,3 as have publications in journals such as Anesthesia & Analgesia.4 Another interesting point raised by Dr Subedi1 is that of the role of private hospitals versus public during the pandemic. Each country will have come to its own solution on this problem. He cites South Korea as being an example of excellent coordination between the 2 sectors. The Republic of Ireland chose a different route which certainly gained public support5 but was not without its challenges.6 In low-income countries, private hospitals may be much better equipped than public hospitals; in such cases, governments will need to negotiate with them as to how they may best serve their nation’s needs. Finally, there is the issue of inadequate supplies of personal protective equipment (PPE). This has been a problem almost everywhere but nowhere more so than in low-resource environments. Governments have rapidly reduced barriers to local production. Companies have been very creative but still the deficit exists. Much has been written about how to extend the life of PPE.7,8 Use of proper PPE is essential in protecting HCWs everywhere but especially in countries where they are a scarce commodity to be treasured and safeguarded. As noted in our article,9 the loss of HCWs after an epidemic can be substantial and can have long-lasting effects on the health care systems they serve. The pandemic of COVID-19 is challenging governments, health care systems, and HCWs as never before. We need to support each other as we find our way through this. It seems that the old advice of Semmelweis to wash our hands frequently and the new advice of public health to work together by staying apart will serve us all well. Choon-Looi Bong, MBChB, FRCADuke-National University of Singapore (NUS) Medical SchoolSingaporeYong Loo Lin School of MedicineSingaporeDepartment of Paediatric AnaesthesiaKK Women’s and Children’s HospitalSingapore Christopher Brasher, MBBS, FANZCAUniversity of MelbourneMelbourne, Victoria, AustraliaDepartment of Anaesthesia and Pain ManagementRoyal Children’s HospitalMelbourne, Victoria, Australia Edson Chikumba, MBChB, MMed (Anaesthesia)Department of Anaesthesia and Critical Care MedicineCollege of Health SciencesUniversity of ZimbabweHarare, Zimbabwe Robert McDougall, MBBS, FANZCAUniversity of MelbourneMelbourne, Victoria, AustraliaDepartment of Anaesthesia and Pain ManagementRoyal Children’s HospitalMelbourne, Victoria, Australia Jannicke Mellin-Olsen, MD, DPHWorld Federation of Societies of AnaesthesiologistsLondon, United KingdomBaerum HospitalOslo, Norway Angela Enright, MBBCh BAO, FRCPCDepartment of AnesthesiaUniversity of British ColumbiaRoyal Jubilee HospitalVancouver, British Columbia, Canada[email protected]

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)0.002
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.478
Threshold uncertainty score0.745

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0060.003
Open science0.0030.004
Research integrity0.0090.010
Insufficient payload (model declined to judge)0.4780.308

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 head0.052
GPT teacher head0.368
Teacher spread0.316 · 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
Domainnot available
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

Citations3
Published2020
Admission routes2
Has abstractyes

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