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Additional file 1 of Human milk fungi: environmental determinants and inter-kingdom associations with milk bacteria in the CHILD Cohort Study

2020· article· en· W6939466069 on OpenAlexaff

Bibliographic record

VenueFigshare · 2020
Typearticle
Languageen
FieldNursing
TopicInfant Nutrition and Health
Canadian institutionsUniversity of AlbertaUniversity of British ColumbiaUniversity of TorontoMcMaster UniversityUniversity of ManitobaChildren's Hospital Research Institute of Manitoba
Fundersnot available
KeywordsCohortCohort studyBacteriaTable (database)Breast milk

Abstract

fetched live from OpenAlex

Additional file 1: Table S1. Characteristics of mother-infant dyads from the CHILD cohort included in this analysis (N = 271) in comparison with previous bacterial analysis (N = 393). Table S2. Milk characteristics of mother-infant dyads for fungal sequencing. Table S3. Comparison of characteristics of mother-infant dyads from the CHILD cohort included in this study across study cities. Table S4. Most abundant fungal genera (> 1% mean relative abundance) in the human milk microbiota among 58 mothers with detectable milk fungi in the CHILD cohort. Figure S1. Milk bacterial composition outlier. Figure S2. Association of milk bacterial clusters and bacterial composition outliers with fungal richness and diversity tested by ANOVA.

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)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.206
Threshold uncertainty score0.293

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.034
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0020.000
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.7940.065

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 head0.031
GPT teacher head0.272
Teacher spread0.240 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

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
Published2020
Admission routes1
Has abstractyes

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