Bibliographic record
Abstract
TRIBE CHRYSOPINI Schneider, 1851 Chrysopina Schneider, 1851: 35. Type genus: Chrysopa Leach, 1815; original designation. Crisopinos Navás, 1910: 59. 16. Available from: http://www.iczn.org/iczn/index.jsp (October, 2006) Chrysopiscini Navás, 1910: 59. Type genus: Chrysopisca MacLachlan,1875 [to Chrysopa: Brooks and Barnard 1990]. Suarini Navás, 1914: 73. Type genus: Suarius Navás, 1914. Chrysopini Navás, 1914: 76. This tribe, treated here as monophyletic (Winterton and de Freitas 2006), occurs worldwide (Brooks and Barnard 1990; Brooks 1997). This is the largest tribe of Chrysopidae, with more than 30 genera (Brooks 1994). The New World chrysopine fauna contains 12 genera (Monserrat et al. 2001). In Canada, nine genera or subgenera occur, as follows: Ceraeochrysa, Chrysopa, Chrysoperla, Chrysopodes (Neosuarius), Dichochrysa, Eremochrysa (Chrysopiella), Eremochrysa (Eremochrysa), Meleoma, and Nineta; in Alaska, only two genera: Chrysopa, and Chrysoperla.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.066 | 0.026 |
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".