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Record W3133292765 · doi:10.1016/j.eclinm.2021.100757

The brazilian tragedy: Where patients living at the ‘Earth's lungs’ die of asphyxia, and the fallacy of herd immunity is killing people.

2021· article· en· W3133292765 on OpenAlex
Mônica Malta, Steffanie A. Strathdee, Patricia García

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEClinicalMedicine · 2021
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicinePublic healthDeath tollPopulationDemographyPandemicCoronavirus disease 2019 (COVID-19)SocioeconomicsEnvironmental healthNursingSociology

Abstract

fetched live from OpenAlex

The Brazilian COVID-19 pandemic has stretched an already overwhelmed, understaffed and underfunded public health system to the breaking point [1]. Brazil's COVID-19 death toll is the second highest in the world behind only the United States, with more than 8.9 million reported cases and 220,000 deaths [at the time of writing]. In the first wave of COVID-19, between May and June 2020, Amazonas state has registered nearly 19 coronavirus deaths per 100,000 residents, compared to 4 deaths? for all of Brazil.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.123
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.123
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.026
GPT teacher head0.379
Teacher spread0.353 · 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