MétaCan
Menu
Back to cohort
Record W3158330068 · doi:10.1186/s40249-021-00849-w

The precision of epidemiological investigation of COVID-19 transmission in Shanghai, China

2021· article· en· W3158330068 on OpenAlexaff
Ying Shi, Honglin Jiang, Mei-Xia Yang, Lin-Juan Dong, Yue Chen, Yi-Biao Zhou, Qingwu Jiang

Bibliographic record

VenueInfectious Diseases of Poverty · 2021
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 detection and testing
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsContact tracingEpidemiologyMedicineTransmission (telecommunications)OutbreakCoronavirus disease 2019 (COVID-19)Scope (computer science)Environmental healthChinaMedical emergencyDisease transmissionDiseaseFamily medicineVirologyPathologyGeographyInfectious disease (medical specialty)Computer scienceTelecommunications

Abstract

fetched live from OpenAlex

BACKGROUND: Shanghai had a local outbreak of COVID-19 from January 21 to 24. Timely and precise strategies were taken to prevent further spread of the disease. We discussed and shared the experience of COVID-19 containment in Shanghai. PROCESS: The first two patients worked at two hospitals but no staff from the two hospitals were infected. The suspected case and his two close contacts were confirmed to be infected within 12 h. The testing rate of individuals was low. The scope of screening was minimized to two related districts and the close contact tracing was completed within 12 h, which were precise and cost-effective. CONCLUSIONS: Active monitoring, precise epidemiological investigation and timely nucleic acid testing help discover new cases, minimize the scope of screening, and interrupt the transmission.

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 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)0.000
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.036
GPT teacher head0.325
Teacher spread0.289 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations19
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueInfectious Diseases of PovertySame topicSARS-CoV-2 detection and testingFrench-language works237,207