Symptomology, prevalence, and impact of <i>Hop latent viroid</i> on greenhouse-grown cannabis (<i>Cannabis sativa</i> L.) plants in Canada
Bibliographic record
Abstract
The incidence of <i>Hop latent viroid</i> (HLVd) affecting cannabis plants in licenced production facilities in Canada during 2020–2023 was determined by RT-PCR analyses of 15 947 samples from nine provinces. Positive detection ranged from 5.3% to 92% of samples submitted, depending on province and year of sampling. The average country-wide HLVd infection incidence was 25.6%. Symptoms on affected plants varied with plant growth stage, and ranged from asymptomatic to mild leaf curl and mottling on stock (mother) plants and on vegetative plants, to extreme stunting and reduced inflorescence development on flowering plants. All symptomatic and some asymptomatic plants contained a 256 nucleotide RNA fragment with 100% sequence homology to HLVd from GenBank. The viroid was detected in various tissues of stock, vegetative, and flowering plants, including the uppermost leaves, at middle and lower positions in the canopy, and in the roots. The incidence of infection varied with the cannabis genotype. Flowering plants displayed yellowing or darkening of inflorescence leaves surrounding the pistillate flowers. Reductions of 12–42% in inflorescence stem lengths, fresh weights, and plant heights were observed in infected plants compared to noninfected plants, depending on the genotype. Levels of tetrahydrocannabinol (THC) and terpenes in diseased inflorescences were also significantly lower. The development of glandular trichomes which produce and store cannabinoids and terpenes was greatly reduced by HLVd infection. The affected trichomes had shorter stalk lengths and smaller glandular head sizes, and appeared shrivelled upon drying of the inflorescences. Hop latent viroid poses a significant economic threat to the cannabis industry.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Survey of Hop latent viroid prevalence and impact in Canadian greenhouse cannabis; the object is plant disease.
The study investigates viroid infection and its effects in cannabis plants, not research itself.
Plant pathology survey of hop latent viroid in cannabis production; agricultural domain.
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".