Bibliographic record
Abstract
Cicipu ([tʃìtʃípù], ISO 639–3 code awc) is spoken by approximately 20,000 people in northwest Nigeria, with the main language area straddling the boundary between Kebbi and Niger states. The language belongs to the Kambari subgroup (not Kamuku as stated by Lewis, Simons & Fennig 2013) of Kainji (Benue-Congo), although it is heavily influenced by the lingua franca Hausa, in which almost all speakers are fluent. There are several identifiable dialects, with native speakers of Cicipu generally listing seven. Of these, Tirisino is the most prestigious and least endangered dialect, and this is the one presented here. Tikumbasi is the most divergent of the dialects, with the /o/ vowel in the other dialects consistently corresponding to /e/ in Tikumbasi (for example /póːpò/ ‘hello’ ~ /péːpè/, /tʃìkóːtò/ ‘drum’ ~ /tʃìkʷéːtè/). The distinction between /o/ and /ɔ/ has been lost in Tikumbasi.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.141 | 0.045 |
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".