Monitoring of Population of Scolytinae in Olive Culture
Bibliographic record
Abstract
Monitoring of insects is important to analyze the species present in culture of economic interest, to verify the period of highest incidence and quantify the damages caused by the pest insects. Here, we aim to assess the diversity of bark beetles in an olive orchard. The experiment was assessed in fortnightly series throughout a year and conducted with a completely randomized experimental design, consisting of three treatments: T1: homogeneous olive culture; T2: heterogeneous olive culture; T3: border area. An ethanol trap was used for the sampling of bark beetles. The species Hypothenemus eruditus, Xyleborus linearicolis and Hypothenemus seriatus showed greater abundance among the treatments. The decrease of abundance, diversity and dominance of bark beetles occurred in the heterogeneous culture (T2). Homogeneous cultures (T1) are more susceptible to the attack of pest-insects due to the lower ecological balance among associate, predator or parasitoid insects. Border areas (T3) showed an increased diversity of arboreal species, favoring the higher incidence of insects. In spring, there is a greater incidence of bark beetles, what reinforces the need for monitoring during this period. So far, there are no evidences of bark beetles infesting olive trees in the area, or the presence of Phloeotribus scarabaeoides, which is the pest bark beetle of olive cultures.
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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 | 0.000 | 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) | 0.001 | 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".