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Record W7062538794

Through the Lenses of Ray Bankston and Don Shugart: Horse Photos from the University of North Texas Libraries

2015· book· en· W7062538794 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of North Texas Digital Library (University of North Texas) · 2015
Typebook
Languageen
FieldPhysics and Astronomy
TopicParticle Detector Development and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)PortraitHorse racingHorsePhotography
DOInot available

Abstract

fetched live from OpenAlex

The selected Horse Photos in this book represent samples images produced by the two most prolific equine photographers, Ray Bankston and Don Shugart between 1962 and 2000. While Ray Bankston and Don Shugart traveled extensively, many of their clients, including prominent ranches and prestigious performance horse events, were located in Texas, home of the American Quarter Horse Association, the National Cutting Horse Association, and the American Paint Horse Association. In addition to formal portraits of famous horses and their owners and riders, their photo collections also contain never-before-published informal shots of riders and horse-show exhibitors, as well as those of farms, ranches, rodeo arenas, and performance rings of a bygone era. Where available, the dates when horses were photographed are noted, as well as the names of their owners, riders, trainers, and the ranches and farms that represent them.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.132
Threshold uncertainty score0.443

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0050.004
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.1320.066

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 head0.012
GPT teacher head0.163
Teacher spread0.150 · 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
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
Published2015
Admission routes1
Has abstractyes

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