Measurement, analysis, and interpretation of mortality factors in insect survivorship studies, with reference to the spruce budworm, <i>Choristoneura fumiferana</i> (Clem.) (Lepidoptera: Tortricidae)
Bibliographic record
Abstract
Abstract A theory and practical method are developed to evaluate insect survivorship as a continuous process in time and the effects of major factors that determine it, with a view to providing solutions to certain problems in survivorship studies. There are two ways of assessing mortality rates: nominal and marginal. A nominal rate is based on the number tallied in terms of the immediate cause of death; it depends on the method of observation employed and can be inconsistent between studies. A marginal rate is free of such inconsistency. The marginal rate attributable to the union of parasitism and disease is evaluated by frequent sampling in the field and rearing of each batch of samples in the laboratory for a short period of time. Comparing this rate with the field mortality rate, directly evaluated by sampling, determines marginal predation rate. The marginal parasitism and disease rates cannot be determined by observation. A computational method is developed to evaluate their approximate values. A step‐by‐step procedure of numerical calculations with data is provided in an appendix. The accuracy of estimating mortality depends on the frequency of sampling in the field and that of inspecting dead individuals in rearing. How frequently sampling and inspection should be conducted is discussed. The method of assessing parasitism developed here has a great advantage over the conventional method based on dissecting the samples, or rearing them through, that often results in a serious underestimation. Also discussed is the relative importance of mortality factors from the pest control point of view, and the concept of “joint contribution” is introduced. Other practical considerations include transportation of samples; rearing conditions; and how to deal with the “dead‐in‐the‐field” in the samples, the “rearing‐death syndrome,” and the “virtually dead” individuals.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".