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Record W2345827104 · doi:10.21273/horttech04199-18

Evaluation of Watermelon Varieties under Organic Production Practices in Georgia

2019· article· en· W2345827104 on OpenAlexaboutno aff
George E. Boyhan, Suzanne O’Connell, Ryan McNeill, Suzanne P. Stone

Bibliographic record

VenueHortTechnology · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Disease Management Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsCitrullus lanatusMulchOrganic farmingHorticultureOrganic productionAgricultureAgronomyMathematicsGeographyBiologyEnvironmental scienceArchaeology

Abstract

fetched live from OpenAlex

Organic production is a fast-growing sector of agriculture in need of variety evaluations under their unique production systems. This study evaluated 16 watermelon ( Citrullus lanatus ) varieties for their performance characteristics under organic production practices. Plants were grown on plastic mulch-covered beds on land that had been certified organic in accordance with the U.S. Department of Agriculture National Organic Program. Six of the entries were F 1 hybrids; the remaining entries were open-pollinated (OP) varieties. Of the 10 OP varieties, three were considered heirloom varieties, including Cream of Saskatchewan, Georgia Rattlesnake, and Moon & Stars. ‘Georgia Rattlesnake’ was the highest yielding variety and had the greatest average fruit weight. Along with ‘Georgia Rattlesnake’, ‘Nunhems 800’, ‘Nunhems 860’, ‘Orangeglo’, and ‘SSX 8585’ were included in the top five yielding varieties. The top five yielding varieties had fruit size that averaged more than 20 lb. Fruit size correlated with rind thickness, with lighter fruit having thinner rind (Pearson’s correlation, r = 0.779), which is not unexpected. ‘Sangria’ had the greatest average soluble solids content at 11.2%, which was greater than all entries with soluble solids less than 10%.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

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

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 head0.038
GPT teacher head0.266
Teacher spread0.228 · 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

Citations7
Published2019
Admission routes1
Has abstractyes

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