Nunani Avannarlerni imartat minguinnerit
Bibliographic record
Abstract
Nunani Avannarlerni imartat sinerissanik ungusisut avatangiisit mingutinneqarnissaannut ajornartorsiutaalluinnarput. Pinartumik ajornartorsiutaapput immap nammineq uumassusilersornerata ajoqusersimanera, aalisapilunneq kiisalu akuutissat ulorianartut . Baltikip Imartaani inuussutissanik pilersuineq ajornartorsiutini annersaavoq, Nunani Avannarlerni Issittullu imartai uuliamik mingutitsineq, toqunartut avataaniit takkussuuttut ajornartorsiutaapput. Imartat sinerissallu imartai Avannaani Avatangiisit pillugit Iliuusissatut Pilersaarummi 2009-2012 isiginiarneqarput. Avannaani imartat piujuaannartitsinneqarnissaat avatangiisillu illersorneqarsinnaasumik 2020-mi minguitsuunissaat anguniagaavoq. Una allagaqaat oqaluttuanik arfineq marlunnik imaqarpoq, Avannaani misissuisartut ikioqatigiillutik eqqaamiuminillu Europamiuusunit ikiorteqarlutik inuit ajornartorsiutit pilersitaat aaqqiiviginiarsaraat. Anguniakkat pingaarnersaraat erseqqissassallugu, qanoq ililluni immap imminut uumassusilersorata nassuiarnissaa, qanorlu ililluta pisuussutaativut piujuaannatinnissaat. Immap Silaannaallu Pitsaassusaata Suleqatigiiffianit / Immap imminut uumassusilersornerata Suleqatigiiffiata, Nunat Avannarliit Ministeriisa Siunnersuisooqatigiivinit misissuinerit allaaserineqartut tamarmik aningaasaliiffigineqarput.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".