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Record W2092134023 · doi:10.1155/2004/342583

D(—)–Lactic Acid Producing Probiotics, D(—)–Lactic Acidosis and Infants

2004· review· en· W2092134023 on OpenAlexaffvenue
David R. Mack

Bibliographic record

VenueCanadian Journal of Gastroenterology · 2004
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicProbiotics and Fermented Foods
Canadian institutionsChildren's Hospital of Eastern OntarioUniversity of Ottawa
Fundersnot available
KeywordsProbioticDiseaseIngestionBiologyAdverse effectPhysiologyBioinformaticsIntensive care medicineBacteriaMedicineInternal medicineEndocrinologyPharmacologyGenetics

Abstract

fetched live from OpenAlex

There is mounting evidence that ingestion of selected probiotics can modify disease morbidity for specific conditions affecting humans, and there is growing interest in the amelioration or prevention of disease with probiotics. Modulation in gene expression of the cellular elements of the intestinal mucosa and interbacterial interactions are leading theories as to the mechanism whereby probiotics can effect benefit for the host. Furthermore, gene-environmental interactions are considered to be important in the development of disease in those at genetic risk. With the intestinal tract harbouring large numbers of bacteria, alteration of the microbial environment with probiotic microbes is being considered as a controllable factor that may limit disease expression for those at genetic risk. This reasoning has led to interest in the administration of probiotics to infants. However, there are significant developmental changes occurring in many organ systems from the time of parturition and during the first months of life. Because there is little in the published scientific medical literature regarding the effects of long-term administration of probiotics to infants, potential problems must be considered; one such issue is that of administration of D(-)-lactate-producing probiotics. An appraisal of the current knowledge of this potential adverse effect is the subject of this communication.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score0.706

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.026
GPT teacher head0.240
Teacher spread0.213 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

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

Citations63
Published2004
Admission routes2
Has abstractyes

Explore more

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