Anas discors
Bibliographic record
Abstract
Anas discors (MGT): breeds in North America from southern Alaska to central USA and the Gulf Coast. It spends the boreal winter in part of the USA, the Antilles, the Bahamas, Central America and northern South America, including northern Brazil (Carboneras & Kirwan, 2016). In late August it reaches the floodplains of Marajó Island/Pará (PA) and lowlands of Maranhão (MA) (Antas, 1987) probably in non-stop flights originating from its breeding sites. Juveniles banded in Canada and the USA (n = 93) between July and September were recovered in the Brazilian states of Acre (AC), PA, MA, Piauí (PI), Ceará (CE), Rio Grande do Norte (RN), Paraíba (PB), Minas Gerais (MG) and Rio de Janeiro (RJ) between December and February (Mestre et al., 2010; MZUSP 42153 [PA, 1959, January]). In addition, there are records between January and March for Roraima (RR), Amazonas (AM), PA and MA (Azevedo-Júnior, 2007; WikiAves, 2016). However, there are also records for RJ between April and August (Sick, 1997; MZUSP 78523 [1966, May]), as well as for SP (Silva-e-Silva & Olmos, 2007; WikiAves, 2016). For Paraná (PR) (Vallejos et al., 2011) and RS, where it appears to be vagrant, there are records only in November (Belton, 1978). However, the occurrence of this species outside northern Brazil is occasional and irregular.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.048 | 0.023 |
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".