Bibliographic record
Abstract
Cyrtoneuropsis veniseta (Stein, 1904) Distribution. Argentina, Bolivia, Brazil, Colombia, Costa Rica, El Salvador, Guyana, Mexico, Nicaragua, Panama, Peru, Trinidad and Tobago, Venezuela. ARGENTINA, Bompland, -29.8167, -57.4333 (Malloch 1934); BOLIVIA, Maipiri, Chimate (Stein 1911); Maipiri, San Carlos (Stein 1911); Maipiri, Sarampiuni, -15.4167, -68.1167 (Stein 1911); San Ernesto (Stein 1911); BRAZIL, Amazonas, Manaus, -3.1019, -60.0250 (DZUP); Amazonas, Manaus, Reserva Duke, -2.9167, -59.9833 (DZUP); Amazonas, Tabatinga, -4.2525, -69.9381 (MNRJ); Bahia, Encruzilhada, -15.5314, -40.9094 (MNRJ); Espírito Santo, Linhares, -19.3911, -40.0722 (MNRJ); Goiás, Campinas, -22.9056, -47.0608 (MNRJ); Pará, Tucuruí, -3.7661, -49.6725 (DZUP); Paraná, Antonina, -25.4667, -48.8333 (Rodríguez-Fernández 2004); Rio de Janeiro, Paracambi, -22.6000, -43.7125 (Espindola 2006); Rio de Janeiro, Petrópolis, -22.5050, -43.1786 (MNRJ); Rio de Janeiro, Rio de Janeiro, -22.9028, -43.2075 (MNRJ); Rio de Janeiro, Três Rios, -22.1167, -43.2092 (MNRJ); Roraima, Ilha de Maracá, 3.4167, -61.6667 (Carvalho & Couri 1991, MNRJ); Serra Pacaraima, 3.5833, - 60.5000 (DZUP); Santa Catarina, Nova Teutônia, -27.1833, -52.3833 (MNRJ); COLOMBIA, Magdalena, 11.1000, -74.8500 (Snyder 1954a); Rio Frio, 10.6833, -75.2667 (Snyder 1954a); Turbo, 8.1000, -76.7167 (Snyder 1954a); COSTA RICA, San Mateo, Higuito, 9.9272, -84.4969 (Snyder 1954a); EL SALVADOR, San Salvador, San Salvador, 13.6667, -89.1667 (Snyder 1954a); GUYANA, Bartica, Kartabo, 5.7833, -57.6333 (Curran 1934b); Cattle Trail Survey, Takaruni River (Albuquerque 1955f); Cattle Trail Survey, Takaruni River (Malloch 1925); Esequibo, Kangaruma, 5.2778, -59.1875 (Curran 1934b); Potaro-Siparuni, Tukeit, 5.2000, -59.4500 (Curran 1934b); Potaro-Siparuni, Chenapowu Village, 4.9167, -59.5667 (Curran 1934b); Potaro-Siparuni, Kaieteur, 5.0000, -59.5000 (Curran 1934b); Upper Takutu - Upper Eseequibo, Kuyuwini, 1.9786, -59.0000 (DZUP); MEXICO, Chiapas, Tapachula, 14.9000, -92.2500 (Snyder 1954a); NICARAGUA, Carazo, Bioreserva, 11.7200, -86.2100 (Nihei et al. 2009); Gramado, Volcán Mombacho, 11.8400, -85.9600 (Nihei et al. 2009); Managua, Managua, 12.1500, -86.2833 (Snyder 1954a); PANAMA, Canal Zone, Balboa, 8.9500, -79.5500 (Snyder 1954a); Canal Zone, Forte Sherman, 9.4103, -79.9533 (Snyder 1954a, MNRJ); Canal Zone, Ilha Barro Colorado, 9.1772, -79.8322 (Snyder 1954a); Canal Zone, Paraiso, 9.0372, -79.5806 (Snyder 1954a); Canal Zone, Summit, 9.0744, -79.6086 (Snyder 1954a); Canal Zone, Tabernilla Key, 9.1333, -79.8000 (Snyder 1954a); Chiriquí, David, 8.4333, -82.4333 (Snyder 1954a); El Cermino (Malloch 1925); Lago Gatún, 9.2000, -79.9167 (Snyder 1954a); PANAMA, La Chorrara, 8.8500, -79.7667 (Snyder 1954a); Rio Trinidad, 9.0111, -79.9625 (Snyder 1954a); PERU (Stein 1911); TRINIDAD AND TOBAGO, Port of Spain, 10.6500, -61.5167 (Snyder 1954a); VENEZUELA, Distrito Federal, Caracas, 10.5000, -66.9167 (Snyder 1954a).
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".