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Record W4312590717 · doi:10.1017/ash.2022.350

Optimizing the interpretation of <i>Clostridioides difficile</i> two-step diagnostic algorithm results through antimicrobial stewardship

2022· article· en· W4312590717 on OpenAlexafffund
Christopher F. Lowe, Shayan Shakeraneh, Colin Lee, Azra Sharma, Victor C. M. Leung

Bibliographic record

VenueAntimicrobial Stewardship & Healthcare Epidemiology · 2022
Typearticle
Languageen
FieldMedicine
TopicClostridium difficile and Clostridium perfringens research
Canadian institutionsUniversity of British ColumbiaProvidence Health Care
FundersProvidence Health Care
KeywordsClostridioidesAntimicrobial stewardshipIndeterminateStewardship (theology)AntimicrobialMedicineIntensive care medicineAlgorithmInternal medicineMicrobiologyBiologyComputer scienceAntibioticsPolitical scienceMathematicsAntibiotic resistance

Abstract

fetched live from OpenAlex

Over a 4-year period, the antimicrobial stewardship team reviewed all positive (PCR+/Tox+) and indeterminate (PCR+/Tox-) cases with the most responsible physician for classification of patients as infection or colonization. Among 501 indeterminate samples, 213 (43%) were considered to be clinical infection, suggesting the need for ongoing clinical assessment of indeterminates.

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)0.006
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.398
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.003
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 head0.052
GPT teacher head0.352
Teacher spread0.300 · 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.

Study designBench or experimental
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

Citations3
Published2022
Admission routes2
Has abstractyes

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