Nunani issittuni (Arktisimi) pinngortitamut- kultureqarnermullu tunngasut avatangiisit : Kalaallit Nunaanni, Islandimi Svalbardimilu
Bibliographic record
Abstract
Nunani Issittorqarfiusuni Avannarlerni (Arktiskimi) anguniarniakkat unammillernartut Silarsuarmi pinngortitat innarlerneqarsimanngingajattut kingulliit ilaat Nunani Issittoqarfiusuni Avannarlerniipput (Arktisimi), pinngortitarssuamilutassani alianaangaartumiipput kultureqarnermut tunngassusillit eqqaassutissaqarfiit, tupinnangaartumik ukiorpassuit ingerlanerini inuit tamaani isseqisumi tujorminartumilu inuuniarsinnaasimanerannik takussutissaasut. Arktiskimi avatangiisit pinngortitarlu pillugit ulluttinni anguniagassat tassa qulakkiissallugu, suliniutit soorlu pinngortitamit pissamaatitut taasakkatta atornerlunneqarnerat, takornariartitsisarnernik suliaqartarnerit, silamiittarnerit ilisimatusarnerilllu, nungusaataanngitsumik ingerlanneqartarnissaat. Aatsaat taamaaliornikkut pinngortitat allanngorneqanngitsut illersorsinnaassagattigit, pinngortitallu uumassusillit assigiinngiiaarneri atatiinnarneqarsinnaallutik aammalu kultureqarnermut tunngassusillit eqqaassutissaqarfiit asseqanngitsut siunissamut isumannaajarneqarlutik. Nunani Avannarleni Qanoq Iliusissanut Pilersaarusiaq pinngortitaq-eqqaassutissaqarfiillu Arktiskimiittut - Kalaallit Nunaanni, Island-imi Svalbard-imilu akuersissutigineqarsimavoq 1999-mi tunaartarinerullugit Arktiskimi nungusaataanngitsumik ineriartortitsinissat siuarsarneqarnissaat. Siunertaasimavoq pinngortitap-eqqaassutissaqarfiillu ataatsimut isigalugit illersorneqarnissaannut pingaarutilinnik suliniuteqarnissat. Nunat assigiinngitsut akornanni taamak ataatsimut periaaseqarniarneq nutaaliatut isigineqarsinnaavoq. Qanoq Iliusissanut Pilersaarusiq suliarineqarsimavoq assigiinngitsorujussuarni iluarsartuullugu pilersaarusiorluni suliaasimasuni (projektini) qulingiluaasuni, maannakkullu naammassineqareersimasuni. Naammassinerisa inerneri uvani atuagaaqqami allaaserineqarsimapput.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.087 | 0.015 |
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".