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Record W4393386403 · doi:10.3138/jammi-2023-09-08

Impact of climate change on amoeba and the bacteria they host

2024· article· en· W4393386403 on OpenAlexaffvenue
Ashley Heilmann, Zulma Vanessa Rueda, David C. Alexander, Kevin B. Laupland, Yoav Keynan

Bibliographic record

VenueJournal of the Association of Medical Microbiology and Infectious Disease Canada · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLegionella and Acanthamoeba research
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsAmoeba (genus)Climate changeHost (biology)LegionellaBacteriaBiologyEcologyMicrobiologyPaleontology

Abstract

fetched live from OpenAlex

The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention. * Cases of disease due to Legionella are reported to NNDSS as legionellosis, which includes Legionnaires' disease, Pontiac fever, and extrapulmonary legionellosis, but are referred to as Legionnaires' disease in this figure or table (because almost all legionellosis cases reported in the United States are Legionnaires' disease cases). Only cases of Legionnaires' disease reported to SLDSS are included in this figure or table. All cases of legionellosis (i.e., Legionnaires' disease, Pontiac fever, and extrapulmonary legionellosis) reported to SLDSS are included in this figure. Legionnaires' Disease Surveillance Summary Report, United States-2018 and 2019 | 6 NNDSS The Centers for Disease Control and Prevention (CDC) coordinates collection of data on all notifiable diseases, including Legionnaires' disease, from across the United States through NNDSS. NNDSS is a passive surveillance system for case-level data. Clinicians and laboratories report cases to local or state health departments, who then investigate the cases and report selected data to CDC. For this report, NNDSS data are limited to Legionnaires' disease case counts, basic demographics, date of disease occurrence, and jurisdiction of residence. The Summary of Notifiable Infectious Diseases-United States (hereafter referred to as the Morbidity and Mortality Weekly Report (MMWR) annual report) reports the official statistics for U.S. Legionnaires' disease cases reported to NNDSS prior to 2016 (https://www.cdc.gov/mmwr/mmwr_nd/index.html). Provisional NNDSS data on reported notifiable infectious diseases for all years are published weekly on CDC WONDER (https://wonder.cdc.gov/ nndss/nndss_weekly_tables_menu.asp), and finalized, yearly summary data for years after 2015 are published annually on CDC WONDER (https://wonder.cdc.gov/nndss/nndss_annual_tables_ menu.asp). Jurisdictions may report cases of any case status (i.e., confirmed, probable, suspect, and unknown) to NNDSS, but only confirmed cases of Legionnaires' disease from the 50 U.S. states, the District of Columbia, and New York City were included in MMWR annual reports and on CDC WONDER from 2000 through 2019, with the following exceptions:

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.237
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.005
GPT teacher head0.252
Teacher spread0.247 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations10
Published2024
Admission routes2
Has abstractyes

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