Super Mario Bros. [eu] (NES) - 0:22:52 without warps - Freddy Andersson
Bibliographic record
Abstract
Speed run of Super Mario Bros., European version, without warp zones done on September 5 2005. Available in three versions: low quality, normal quality, and 50 fps high quality. Author's comments: Here is a run through 32 stages and it's not have the speed as "AndrewG" and Trevor through their 8 stages. I lost my flower six times but not died on the way. A few mistakes is terrible but i have tried to do it funny, so the run is nice through the first two worlds, I lost my flower on 3-1 and got it back on 3-2... Then problems come in 5-1. This run also give me a lession about how to shoot through bowser (or what should I call him?) in the sixth castle. I don't know how i succeeded without it. I have taken it in slow motion and it is fantastic! I also missed a mushroom in 6-2 that looks funny, I swear you're gonna laugh about it! And if you wonder why I did not take the "pipe way" in the first stage... It's becuse it's not allowed over at TG so I don't want to use it. Maybe you also wonder why I wait on a plattform in 5-3... It's becuse I want to know if the platforms to the left exist this time becuse some time they do not. I don't want to write comments for all 32 stages. Maybe the next speedrun will have it. I have a feeling about someone is gonna do a "Jason Baum" run through this wonderful game some day :D
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.849 | 0.790 |
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; the direct Gemma label and the distilled Codex classifier 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".