Germplasm Evaluation of Tomatillo ( <i>Physalis Ixocarpa</i> Brot.) Cropped Under Ontario, Canada and Chapingo, Mexico Environmental Conditions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Germplasm Evaluation of Tomatillo ( Physalis Ixocarpa Brot.) Cropped Under Ontario, Canada and Chapingo, Mexico Environmental Conditions Evaluation of five tomatillo Mexican landraces including altogether 13 accessions was performed under environmental conditions of Ontario, Canada and Chapingo in central Mexico. The measured traits were: beginning of flowering and harvest, total number of harvested fruits and the yield. Number of days to flowering or fruiting was counted from the date of planting. In both localities accessions 1 and 3 of the Rendidora landrace as well as the accession 1 of the Manzano landrace were the earliest and the highest yielding. In Chapingo the accession 1 of the Rendidora landrace gave the yield of fruits almost 4 kg.m -2 , in Elora, Canada the same accession was also the best and yielded almost 3 kg.m -2 . In general, all accessions were earlier in Elora than in Chapingo; yield in both localities was in general similar except the landrace Milpero obviously poorly suited to Canadian environment. Tomatillo may be considered as a promising new crop for Ontario, Canada agriculture. Yield was correlated negatively, in a significant way, with the number of days to flowering and harvest, it means that the development of early, highly productive varieties by artificial selection is feasible.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it