Bibliographic record
Abstract
This is Wikipedia Weekly, Episode 1 for the week of October 16, 2006. 1. Introduction of the panel * Andrew Lih User:Fuzheado, active on English Wikipedia located in China. Currently writing a book about Wikipedia and its community. * Andrew2 aka User:Tawker, of Tawkerbot2 and currently located in Canada. Is not writing a book about Wikipedia yet... his blog isn't paper worthy yet * I think in this podcast, we'll go by Wikipedia usernames, because there are way too many Andrews in the Wikipedia universe. 2. Introduction to news sources * Signpost, started by Michael Snow * Wikizine, by walter (http://www.wikizine.org/) * Wikipedia:Announcements 3. Latest news * Board elections - Erik Moeller elected, Kat/Mindspillage and Oscar next. * Taiwan location for Wikimania 2007 * Chinese unblocking Wikipedia * Tor blocking.... is it a good pratice * No more @ signs in usernames, because of spamming, breaks stuff - [username@foobar.com] - New accounts on the WMF-wikis can not longer be created if the username contains the @-symbol. Existing users who have that symbol in there username can still login but only temporary. All these users need to request for a username change. Contact a local bureaucrat to do that or ask a steward if your wiki does not have a bureaucrat. o http://meta.wikimedia.org/wiki/Requests_for_permissions#Username_changes * [CategoryTree] - On the category-pages there is now a function added that lets users browse through the lower category levels from the higher category. There is an option to "expand" the category. This makes it much more easy to navigate and find the category you are looking for without the need to actually request the different layers of the category. This function works only if javascript is enabled. If not, the "+" symbol appears but does not work. Those users can still use the categories the traditional way. * Bot commons delinker * http://en.wikipedia.org/wiki/User:Wherebot - Copyvio finding bot * Polar exploration improvement Wikipedia:Spotlight/work before 4. Special:Random article + discussion 5. Articles deleted NY Times article (free registration required) 6. Listener feedback * Leave on WP:WWPC - We'll add an option to leave a voicemail for Q & A later. If you have any questions please feel free to post in the show comments and we'll respond on a QA session. 7. Regular Segments * The World According to Wikipedia [1] 8. Lost (TV series) 11. Amish 12. YouTube 13. World War II 14. PlayStation 3 16. United States 18. North Korea 20. List of big-bust models and performers 21. Sexual intercourse 22. Naruto 25. Mortal Kombat: Armageddon 26. Christopher Columbus 27. List of sex positions 28. Wii 29. Japan 30. Sex 31. September 11, 2001 attacks 32. 2006 North Korean nuclear test 33. List of female porn stars 34. X-Men 35. List of South Park episodes 36. Deaths in 2006 37. Mark Foley 38. Clitoris 39. South Park 40. The Lord of the Rings 41. Windows Vista 42. Penis 43. Special:Booksources 44. France 45. List of Naruto episodes 46. Cory Lidle 47. Mexico 48. Masturbation 49. Make Love, Not Warcraft 50. Nuclear weapon#* Stats/numbers
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 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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.240 | 0.008 |
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".