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Record W2027732582 · doi:10.4056/sigs.4187859

The Hospital Microbiome Project: Meeting report for the 2nd Hospital Microbiome Project, Chicago, USA, January 15th, 2013

2013· article· en· W2027732582 on OpenAlexaff
Benjamin D. Shogan, Daniel P. Smith, Aaron I. Packman, Scott T. Kelley, Emily Landon, Seema Bhangar, Gary J. Vora, Rachael M. Jones, Kevin Keegan, Brent Stephens, Tiffanie Ramos, Benjamin C Kirkup, Hal Levin, Mariana Rosenthal, Betsy Foxman, Eugene B. Chang, Jeffrey A. Siegel, Sarah Cobey, Gary An, John C. Alverdy, Paula Olsiewski, Mark O. Martin, Rachel Marrs, Mark Hernandez, Scott Christley, Michael J. Morowitz, Stephen G. Weber, Jack A. Gilbert

Bibliographic record

VenueStandards in Genomic Sciences · 2013
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntibiotic Use and Resistance
Canadian institutionsUniversity of Toronto
FundersUniversity of ChicagoAlfred P. Sloan Foundation
KeywordsMicrobiomeHuman Microbiome ProjectMedicineBiologyBioinformaticsHuman microbiome

Abstract

fetched live from OpenAlex

This report details the outcome of the 2nd Hospital Microbiome Project workshop held on January 15 th at the University of Chicago, USA.This workshop was the final planning meeting prior to the start of the Hospital Microbiome Project, an investigation to measure and characterize the development of a microbial community within a newly built hospital at the University of Chicago.The main goals of this workshop were to bring together experts in various disciplines to discuss the potential hurdles facing the implementation of the project, and to allow brainstorming of potential synergistic project opportunities.

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)0.024
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.039
Threshold uncertainty score0.131

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.011
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0020.001
Scholarly communication0.0050.002
Open science0.0020.006
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0390.022

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 head0.012
GPT teacher head0.280
Teacher spread0.269 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations13
Published2013
Admission routes1
Has abstractyes

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