Comparison of <i> <scp>B</scp> otrytis cinerea </i> airborne inoculum progress curves from raspberry, strawberry and grape plantings
Bibliographic record
Abstract
Airborne B otrytis cinerea conidia concentration was monitored using a new q PCR assay in strawberry, raspberry and grape plantings in 2010, 2011 and 2012. Airborne inoculum progress curves ( IPC s) were constructed and analysed using the maximum ACC ( Y max ), ACC during the flowering period ( Y f ), and area under the IPC ( AUIPC std ) and descriptors derived from fitting growth models. The structure of IPC s was examined by conducting multivariate principal component analyses. The dimensionality of the data was reduced to two principal components ( PC s) accounting for 86·12% of the variation. All descriptors derived from growth models were associated with PC 1 and descriptors derived directly from the data were associated with PC 2. Based on principal component analysis, the structure of the IPC s varied with the crop, with AUIPC std values of 28·18, 42·79 and 155·83 and Y f values of 53·58, 20·14 and 142·54 conidia m −3 h −1 in raspberry, strawberry and grape, respectively. Time to 50% of the maximum inoculum concentration was lower in raspberry and strawberry than in grape. The IPC s monitored in raspberry were characterized by narrow ranges for mean absolute rate (0·012–0·016) and AUIPC std (16·80–48·85), the IPC s monitored in strawberry were characterized by wide ranges for mean absolute rate (0·031–0·080) and AUIPC std (12·31–98·39), and the IPC s monitored in grape crops were characterized by a lower mean absolute rate (0·006–0·012) and a higher AUIPC std (50·95–335·14).
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How this classification was reachedexpand
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 | 0.000 |
| 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) | 0.001 | 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".