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Record W2171983868 · doi:10.21273/horttech.22.2.169

Survey of Ornamental Nurseries in Florida Participating in the U.S.-Canadian Greenhouse Certification Program

2012· article· en· W2171983868 on OpenAlexaboutno aff
Joyce L. Merritt, E. R. Dickstein, R. S. Johnson, Michael P. Ward, Robert J. Balaam, Carrie L. Harmon, Philip F. Harmon, Gul Shad Ali, Aaron J. Palmateer, Timothy S. Schubert, A.H.C. van Bruggen

Bibliographic record

VenueHortTechnology · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsnot available
Fundersnot available
KeywordsCertificationGreenhousePlan (archaeology)BusinessAgricultural scienceGeographyPolitical scienceEnvironmental scienceBiologyArchaeologyAgronomy

Abstract

fetched live from OpenAlex

The purpose of this study was to evaluate the U.S.-Canadian Greenhouse Certification Program (USGCP) that was initiated in 1998. A survey consisting of 34 questions was designed and 43 out of ≈48 nurseries in Florida participating in the USGCP were visited. Based on the answers to the questionnaire, most of the nurseries were in compliance with the majority of USGCP requirements, growers were satisfied with the program, and there was an economic benefit to participating in the program. The main problems identified were the ambiguous wording of some of the requirements and the impracticality of keeping imported and domestic plants completely segregated. Moreover, many of the respondents did not have a written description of a pest management plan. Chi square statistical analysis showed that there was almost no difference between nursery groups in their responses to the majority of the survey questions, indicating that the USGCP is a successful program for both large and small nurseries. This quantitative assessment of the USGCP is the first assessment conducted for this program and discussed in a peer-reviewed publication.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.704
Threshold uncertainty score0.595

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.037
GPT teacher head0.278
Teacher spread0.241 · 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 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

Citations5
Published2012
Admission routes1
Has abstractyes

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