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Record W3121727041

Strategic Analysis of the U.S. Quarter Horse Industry, Emphasizing California

2011· article· en· W3121727041 on OpenAlexaboutno aff
Jon C. Phillips, Flynnie Kolb, Chelsea Bicknell

Bibliographic record

VenueKagoshima Daigaku Kogakubu Kenkyu Hokoku · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)AttractivenessMarketingBreedBusinessAgricultureAgribusinessAgricultural economicsEconomicsGeography
DOInot available

Abstract

fetched live from OpenAlex

The American Quarter Horse is the most popular breed of horse in California, as well as nationwide. This breed has shaped agricultural history and has had a major impact on the agricultural economy because. The objective of this report is to provide strategic information about the U.S. quarter horse industry, with an emphasis on California. This report provides information on the following topics: statistics of the industry, quarter horse associations, trends in the industry, prevailing marketing practices, innovative/successful marketing practices, success factors for horse businesses, and characterization of related and supporting industries. The primary contribution of the report is a diagram and description of the horse industry supply chain. The varying levels of entry barriers and varying degrees of attractiveness to potential entrants are given for many types of businesses in the horse industry.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.179
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0170.002

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 head0.035
GPT teacher head0.239
Teacher spread0.204 · 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; both teacher heads agree on what is shown here.

Study designObservational
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

Citations0
Published2011
Admission routes1
Has abstractyes

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