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Record W4385991482 · doi:10.1039/d3ew00278k

<i>Legionella pneumophila</i> occurrence in reduced-occupancy buildings in 11 cities during the COVID-19 pandemic

2023· article· en· W4385991482 on OpenAlex

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

VenueEnvironmental Science Water Research & Technology · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLegionella and Acanthamoeba research
Canadian institutionsPolytechnique Montréal
FundersDivision of Chemical, Bioengineering, Environmental, and Transport SystemsEidgenössische Anstalt für Wasserversorgung Abwasserreinigung und GewässerschutzRoyal SocietyHorace H. Rackham School of Graduate Studies, University of MichiganUniversity of PittsburghUniversity of MichiganPurdue UniversityArizona State UniversityWater Research FoundationRoyal Society of ChemistryNational Science Foundation
KeywordsPandemicLegionella pneumophilaLegionellaCoronavirus disease 2019 (COVID-19)Occupancy2019-20 coronavirus outbreakGeographySevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Environmental healthVirologyMedicineBiologyOutbreakInfectious disease (medical specialty)Ecology

Abstract

fetched live from OpenAlex

Legionella pneumophila was quantified during the COVID-19 pandemic in 26 buildings in three countries to identify factors that influenced positivity.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.223
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.005
Scholarly communication0.0000.000
Open science0.0020.002
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 head0.042
GPT teacher head0.337
Teacher spread0.294 · 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