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Specimen Selection, Collection, and Transport for Anaerobic Culture

2023· other· en· W4406364734 on OpenAlexaff
Melphine Harriott

Bibliographic record

VenueClinMicroNow · 2023
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial Identification and Susceptibility Testing
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsData collectionAnaerobic exerciseHealth careClinical microbiologyMedical emergencyMedicineComputer scienceOperations managementMicrobiologyBiologyEngineering

Abstract

fetched live from OpenAlex

Abstract Proper collection of specimens, to avoid contamination with organisms of the normal microbiota, and prompt transport to the laboratory for processing are essential. This is especially true for specimens sent to the laboratory for anaerobic culture. The laboratory director and staff must provide health care personnel with guidelines for the optimal type and amount of clinical specimens that are needed for anaerobic culture, including the appropriate methods for specimen collection. Patient care units, clinics, emergency rooms, and satellite facilities should be provided with appropriate collection and transport devices and complete instructions for their use. The ideal transport system should maintain the viability of the anaerobes during transport without allowing the overgrowth of members of the normal microbiota that are not a part of the pathogenic process. Good communication between the clinical microbiology laboratory and the clinical staff will ensure that collection and transport are optimal.

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)0.004
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: Other · Consensus signal: Other
Teacher disagreement score0.112
Threshold uncertainty score0.373

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1120.090

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 head0.014
GPT teacher head0.269
Teacher spread0.255 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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