[[**LIVE@STREAM**]]" Edmonton Oilers vs Florida Panthers Live Free Broadcast
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Edmonton Oilers is playing against Florida Panthers on Nov 29, 2022 at 2:30:00 AM UTC.\n\n\nThe game is played at Rogers Place. This game is part of NHL.\n\n\n\n\nCLICK HERE TO WATCH LIVE\n\n\nCLICK HERE TO WATCH LIVE\n\n\n\nHere you can find previous Edmonton Oilers vs Florida Panthers results sorted by their H2H games. SofaScore also allows you to check different information regarding the match, such as:\n\n\nDue to the releafsvvance of the CdadOVID-19 global pandemic, we are releasing our dataset of tweests acquired from the Twitter Stream related to COVID-19 sfaschatter. Since our first release we have received additional data frodhdthm our new collaborators, allowing this resource to grow to its current size. Dedifadcated data gathering started from March 11th yielding over 4 millionadad tweets a day. We have addewwe coverage. Version 10 added ~1.5 million tweetsxzgsf in the Russian language collected between January 1st aadadnd May 8th, gracefully provided to us by: Katya Artemova (NRU HSE) and Elena Tutubalina (KFU). From version 12 we have included daily hashtags, mentions and emojis and their frequencies the respective zip files. From version 14 we have included the tweet identifiers and their respective language for the clean version of the dataset. Since version 20 we have included language and place location for all tweets.\n\n\nThe data collected from the stream captures all languages, but the higher prevalence are:  English, Spanish, and French. We release all tweets andada retweets on the full_dataset.tsv file (1,371,993,942 unique tweets), and a cleaned version with no retweets on the full_dataset-clean.tsv file (355,6weqwrwq91,266 unique tweets). Therfawde are several practical reasons for us to leave the retweets, tracing important tweets and their dissemination is one of them. For NLP tasks we provide the top 1000 frequent terms in frdadequent_terms.csv, the top 10sdasfd00 bigrams in frequent_bigrams.csv, and the top 1000 trigrams in frequent_trigrams.csv. Some general statistics per day are included for both datasets in the full_dataset-statistics.tsv and full_dataset-clean-statistics.tsv files. For mofsre statistics and some visualizations visit: http://www.panacealab.org/covid19/\n\n\nMore details can be found (and will be updated faster at: hfsttps://github.com/thepanacfealab/codadavid19_twitter) and our pre-print about the dataset (https://arxiv.org/abs/2004.03688)\n\n\nAs always, the tweetsaadea distributed here are only tweet identifiers (with date and time added) due to the terms and conditions of Twitter to re-distribute Twitter data ONLadY for research purposes. They need to be hydrated to be used.arwetsef
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.006 |
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 it