Bibliographic record
Abstract
Most families in the hemipteran suborder Heteroptera contain at least some species of zoophages. If Henry and Froeschner’s (1988) accounting of U.S. and Canadian Heteroptera reflects worldwide proportions, 65% of all families in this suborder are partially or entirely composed of carnivorous species. Although consideration of the original (carnivorous or phytophagous) trophic habits of this group makes for a fascinating discussion (see Cobben 1979; Sweet 1979; Schaefer 1993, 1997; Cohen 1996, 1998a,b), the purpose here is to describe the nature of the feeding method as it pertains to carnivory. No suggestions about the origin of predation or phytophagy in the Heteroptera will be made. Also avoided will be another related and equally fascinating area of discussion: that many heteropterans are well adapted for straddling both phytophagous and carnivorous feeding niches (Rastogi 1962, Slater and Carayon 1963, Ridgway and Jones 1968, Tamaki and Weeks 1972, Bryan et al. 1976, Wheeler 1976, Cobben 1978, Braimah et al. 1982). This explanation of the feeding method in predaceous Heteroptera should clarify some misunderstandings, misconceptions, and oversimplifications of a delightfully complex and efficient process.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".