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Record W2589293839 · doi:10.1128/jcm.02290-16

Correction for Vasireddy et al., Mycobacterium arupense, Mycobacterium heraklionense, and a Newly Proposed Species, “Mycobacterium virginiense” sp. nov., but Not Mycobacterium nonchromogenicum, as Species of the Mycobacterium terrae Complex Causing Tenosynovitis and Osteomyelitis

2017· erratum· en· W2589293839 on OpenAlexaff
Ravikiran Vasireddy, Sruthi Vasireddy, Barbara A. Brown‐Elliott, Nancy L. Wengenack, Uzoamaka A Eke, Jeana L. Benwill, Christine Y. Turenne, Richard J. Wallace

Bibliographic record

VenueJournal of Clinical Microbiology · 2017
Typeerratum
Languageen
FieldMedicine
TopicMycobacterium research and diagnosis
Canadian institutionsSaskatchewan Disease Control Laboratory
Fundersnot available
KeywordsMycobacteriumMicrobiologyMycobacterium abscessusMycobacterium chelonaeTenosynovitisMycobacterium marinumMycobacterium avium complexMycobacterium InfectionsBiologyMedicineBacteriaGenetics

Abstract

fetched live from OpenAlex

Volume 54, no. 5, p. [1340–1351][1], 2016, . Page 1349, column 1: The last three paragraphs preceding the Acknowledgments section should be replaced with the following. Mycobacterium virginiense (vir.gi.ni.en′se. N.L. neut. adj. virginiense, of or

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)0.004
metaresearch head score (Gemma)0.062
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 score0.060
Threshold uncertainty score0.200

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.062
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.002
Science and technology studies0.0030.002
Scholarly communication0.0030.003
Open science0.0030.002
Research integrity0.0040.009
Insufficient payload (model declined to judge)0.0600.032

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 head0.061
GPT teacher head0.351
Teacher spread0.290 · 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

Citations11
Published2017
Admission routes1
Has abstractyes

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