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Molecular Methods for Identification of Microorganisms

2023· other· en· W4406352197 on OpenAlexaff
Alexander L. Greninger, David R. Hillyard, L G Reimer, Ninad Mehta, Melanie A. Mallory, Robert Schlaberg, Matthew A. Pettengill, Yi‐Wei Tang, Nang L. Nguyen, Benjamin A. Pinsky, Ted E. Schutzbank, Erin H. Graf

Bibliographic record

VenueClinMicroNow · 2023
Typeother
Languageen
FieldMedicine
TopicHerpesvirus Infections and Treatments
Canadian institutionsRoyal University Hospital
Fundersnot available
KeywordsHerpes simplex virusVirusVirologyAntibodySalivaBiologyImmunologySubfamilyMedicineInternal medicineGeneGenetics

Abstract

fetched live from OpenAlex

Abstract Human immunodeficiency virus‐1 (HIV‐1) ribonucleic acid is most often used for confirmation of HIV‐1 infection down stream of fourth‐generation antigen‐antibody screening assays and for quantitative viral load monitoring. For individuals with virologic failure, resistance testing is recommended at designated plasma viral concentrations, which are routinely monitored as part of patient care. Whole blood and plasma are acceptable specimen types for HIV resistance testing. Human papillomavirus types infecting the mucosal squamous cell epithelium are categorized into three general groups: the high‐risk (HR) group, the low‐risk (LR) group, and members of the indeterminate risk group for which insufficient information exists for classification as the HR or LR type. Herpes simplex virus 1 (HSV‐1), HSV‐2, and varicella‐zoster virus are members of the alphaherpes virus subfamily that exhibit neurotropism.

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)0.002
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.041
Threshold uncertainty score0.136

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0410.070

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 head0.027
GPT teacher head0.417
Teacher spread0.391 · 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
GenreMethods

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

Citations0
Published2023
Admission routes1
Has abstractyes

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