An Inexpensive Feeding Bioassay Technique for Stored-Product Insects
Bibliographic record
Abstract
ABSTRACT We used the red flour beetle, Tribolium castaneum Herbst (Coleoptera: Tenebrionidae), to compare three feeding bioassay techniques using flour disks. The area (scanner or digital photographs) and mass (sensitive balance) of the same flour disks were measured daily for 1 or 2 wk to assess feeding by insects. The loss in mass and area over 4 h was measured, as some variation over time was noticed in the disks with no insects feeding on them. The gravimetric method correlated well with both measurements of the area for the disks held in a growth chamber: scanner (R2 = 0.96), digital photography (R2 = 0.96). There was also a high correlation (R2 = 0.86) between the disk weight and area scanned at normal lab conditions. There were differences in the percentage of the disks remaining over time depending on the temperature and whether they were weighed or scanned. Measuring the mass of the disks resulted in a relatively larger percent of disk remaining compared with the scanned area. Mass measurements required a sensitive balance, handling of the disks and the insects, and appeared slightly more sensitive to humidity and temperature changes over time. Scanning the disks requires flat bed scanner access but less handling of both insects and disks. Digital photographs could be taken quickly, requiring less equipment, although photographs had to be further processed to determine area Scanning or taking digital photographs of flour disk area was an effective technique for measuring insect feeding.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".