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Record W2978305916 · doi:10.3390/microorganisms7100418

Reply to Comments on “Shiga-Toxin Producing Escherichia coli in Brazil: A Systematic Review. Microorganisms 2019, 7, 137”

2019· article· en· W2978305916 on OpenAlexaff
Vinícius Silva Castro, Eduardo Eustáquio de Souza Figueiredo, Kim Stanford, Tim A. McAllister, Carlos Adam Conte‐Júnior

Bibliographic record

VenueMicroorganisms · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEscherichia coli research studies
Canadian institutionsAgriculture and Agri-Food CanadaAgriculture Food and Rural Development
FundersFundação de Amparo à Pesquisa do Estado de Mato GrossoFundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de JaneiroConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsEscherichia coliMicrobiologyShiga toxinMicroorganismToxinBiologyBacteriaGenetics

Abstract

fetched live from OpenAlex

Recently a comment regarding our article entitled “Shiga-Toxin Producing Escherichia coli in Brazil: A Systematic Review” was made by Dr [...]

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)0.022
metaresearch head score (Gemma)0.142
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.026
Threshold uncertainty score0.118

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.142
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0030.003
Science and technology studies0.0030.003
Scholarly communication0.0040.004
Open science0.0030.004
Research integrity0.0260.022
Insufficient payload (model declined to judge)0.0130.006

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 head0.007
GPT teacher head0.273
Teacher spread0.266 · 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
GenreCommentary

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

Citations8
Published2019
Admission routes1
Has abstractyes

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