Ceratochodaeus eliotti Huchet 2019, new combination
Bibliographic record
Abstract
New data on the distribution of Ceratochodaeus eliotti (Huchet, 2014), new combination Initially described from Mindanao, C. eliotti is known from several localities: Bukidnon, Cabanglasan (type locality), Mount Kalatungan, Dominorog and Lanao del Sur (Wao). Among the specimens originated from the Royal Ontario Museum, two males, collected in Leyte island at 7 km N of BayBay, Pangasugan (250 m), 10°45’N / 124° 50’E, between 28-30 may 1987 (ROM 873055), could be indisputably related to this species (Fig. 12). Both specimens were collected using a Malaise trap placed on a slope, above a disturbed forest area actively logged and partially burned (Fig. 13). From a biogeographic point of view, this interesting discovery testifies of close relationships between Mindanao and Leyte. As noticed by Racheli and Biondi (1989), the southern islands (Cebu, Leyte and Bohol) present a high faunistic affinity with Mindanao, while the northern ones (Mindoro, Panay, Samar and Negros) are more similar to Luzon. During the late Pleistocene period of low sea level (from 126,000 (± 5,000) to 11,700 years ago), many Philippine islands were more extensive, with groups connecting into larger islands. Mindanao, Samar, Leyte, and Bohol were all one island referred to Greater Mindanao and their faunal affinities to each other persist to this day (Heaney 1986; Heaney and Regalado 1998; Peterson et al. 2000).
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".