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Record W3006856838 · doi:10.1177/1040638720907586

Sterile traumatic panniculitis in a captive Brent goose

2020· article· en· W3006856838 on OpenAlexaff
Marie‐Odile Benoit‐Biancamano, Isabelle Langlois

Bibliographic record

VenueJournal of Veterinary Diagnostic Investigation · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicMicrobial infections and disease research
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPanniculitisGooseBrantaFeatherBiologyHistologyPathologyGiant cellMultinucleateAnatomyZoologyMedicineEcology

Abstract

fetched live from OpenAlex

) with a history of severe feather picking by its mate, was presented with 0.5-2.5 cm skin nodules on the head and neck. Histologic examination revealed a well-delineated dermal mass that surrounded an intact feather follicle and was composed of lakes of proteinaceous fluid and fibrin with scattered foamy macrophages and multinucleate giant cells. No bacteria or fungi were identified with histology, microbial culture, or PCR. Sterile panniculitis is an infrequent finding in animals and traumatic panniculitis is rarely sterile.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.069
GPT teacher head0.299
Teacher spread0.230 · 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 designCase report
Domainnot available
GenreEmpirical

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

Citations1
Published2020
Admission routes1
Has abstractyes

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