Scolopendra dehaani Brandt 1840
Bibliographic record
Abstract
Scolopendra dehaani Brandt, 1840 Terra typica: “ Java ” (Indonesia). Recent material from Martinique. Absent. Additional material. Japan, Оkinawa, 2 ad. (ZMMU, Rc 6293); Cambodia, Rattanakiri Province, 1 ad. (ZMMU, Rc 7004); Indonesia, Sumatra Island, Sumatera Utara, 1 sad. (ZMMU, Rc 7089); Vietnam: Vinh Phuk Province, 1 spm (ZMMU, Rc 6299) + Dong Nai Province, 1 ad. (ZMMU, Rc 8006). Diagnosis. See Siriwut et al. (2016: 51). Range (after Schileyko 2007: 76, corrected). Widespread in Southeast Asia; Japan (Okinawa Island), China (recorded from Hong Kong and Hainan), Malay Peninsula, Singapore, Indonesia (Sumatra, Java), Myanmar (Burma), Thailand, Vietnam, Laos, Cambodia, Bangladesh, Sri Lanka, Philippines, Andaman and Nicobar Islands, India (Western and Eastern Himalaya). Remarks. This South Asian species is introduced to many islands and coastal areas of the New World. As for Martinique, this large and well-recognizable species is not found recently on the island, thus it is reasonable to think that it does not occur in Martinique at present. Thus, we suppose that historical New World record of S. dehaani made by Kraepelin 1904 (p. 324) for Martinique, Ile-de-France (France), Florida and Salabury (probably Salaberry, Québec, Canada) were obviously based on introduced (but not acclimatized) specimens.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 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".