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Record W6976976609 · doi:10.6084/m9.figshare.25045549

Additional file 1 of Characterization of the hoof bacterial communities in feedlot cattle affected with digital dermatitis, foot rot or both using a surface swab technique

2024· article· en· W6976976609 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFigshare · 2024
Typearticle
Languageen
FieldComputer Science
TopicComputational Physics and Python Applications
Canadian institutionsUniversity of CalgaryOlds CollegeUniversity of SaskatchewanAgriculture and Agri-Food Canada
Fundersnot available
KeywordsHoofLesionFibre typeFoot rotTable (database)Digital image analysis

Abstract

fetched live from OpenAlex

Additional file 1: Table S1. Biological information of cattle sampled in this study. Health status refers to whether an animal has hoof disease/lesions. Healthy animals without any hoof lesions (which provided CH control samples) were from feedlot A. Table S3. Beta diversity analysis of PERMANOVA pairwise comparison between lesion type and control skin groups (final categories) based on weighted Unifrac distance metric. Table S4. The top 15 associated taxa with each hoof lesion type in Songbird analysis. Single-underlined taxa were associated with at least two lesion types, and double-underlined taxa were associated with all three lesion types. Table S5. Distribution of different M-stages of lesions in DD-lesion and DD+FR lesion samples, using the Dopfer (1997) M-stage 5-point classification system across three feedlots. M-stage only applies to the DD lesion in the DD+FR lesions. No M3 and only one M1 lesion were observed in trial period.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.505
Threshold uncertainty score0.748

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.2530.000

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 head0.024
GPT teacher head0.233
Teacher spread0.209 · 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