Neusticurus ecpleopus Cope 1876
Bibliographic record
Abstract
NEUSTICURUS ECPLEOPUS SPECIMENS EXAMINED Dry skulls. Collected in Peru (mostly in the Rio Cenepa area, except as indicated); measurements are from tip of premaxilla to posterior edge of supraoccipital: MVZ 163395, 11.7 mm; MVZ 163397, 12 mm; MVZ 163389, 12.1 mm; MVZ 174957, 12.2 mm (Rio Santiago); MVZ 163390, 12.3 mm; MVZ 174956, 13.5 mm (Rio Santiago); MVZ 163400, 14 mm; MVZ 163388, 14.5 mm; MVZ 163395, 15.1 mm; MVZ 163410, 16.1 mm; and MVZ 163394, disarticulated. Cleared and double-stained specimens. Specimen SVLs are followed by sex, where known, and percentage maximum size based on that reported for each sex by Sherbrooke (1975) (average of male and female maximum sizes used to calculate percentage in specimens where sex is unknown): KU 48246, 22.4 mm SVL (33%), Napo, Ecuador; USNM 316870, 22.9 mm SVL (34%), Amazonas, Peru; KU 109803, 23.6 mm SVL (35%), Napo, Ecuador; MVZ 163166, 23.6 mm SVL (35%), Peru; KU 148251, 25.8 mm SVL (male, 36%), Napo, Ecuador; MVZ 174949, 26.7 mm SVL (40%), Peru; KU 109781, 27.3 mm SVL (male, 38%), Napo, Ecuador; MVZ 174920, 28.7 mm SVL (female, 46%), Peru; KU 109809, 28.9 mm SVL (female, 47%), Napo, Ecuador; MVZ 174928, 30.5 mm SVL (female, 49%), Peru; MVZ 174905, 31.8 mm SVL (female, 51%), Peru; KU 109789, 32.9 mm SVL (female, 53%), Napo, Ecuador; MVZ 163147, 34.3 mm SVL (male, 48%), Peru; MVZ 174901, 37.9 mm SVL (57%), Peru; MVZ 174899, 39 mm SVL (female, 63%), Amazonas, Peru; MVZ 163185, 40.7 mm SVL (female, 66%), Peru; MVZ 174953, 45.2 mm SVL (male, 63%), Amazonas, Peru; MVZ 174896, 47.6 mm SVL (female, 77%), Peru; MVZ 163187, 51.1 mm SVL (male, 71%), Amazonas, Peru; MVZ 163145, 55.6 mm SVL (male, 77%), Amazonas, Peru; MVZ 163202, 59.1 mm SVL (female, 95%), Peru; MVZ 174891, 63.2 mm SVL (male, 88%), Amazonas, Peru.
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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 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 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".