Bibliographic record
Abstract
We are currently nine weeks into the season and it has absolutely flown by.We are getting down to the last few weekends of G-MAC play which means we are getting closer to tournament time!But before I get ahead of myself, I!ll tell you a little bit about our three-match campaign this past weekend.The team finished up mid-term week on Wednesday and headed into "Fall Break" ready to play some volleyball in West Virginia!!We left campus at 11 a.m. on Thursday morning embarking on our adventure.We took our time and made a pit stop for lunch at Panera (YUM!), one of our favorite places to eat!We relaxed in the bus (aka our second home) and did homework until we arrived at Alderson Broaddus for our first match of the weekend.We started the match fantastic in set one and maybe became a bit too confident and ran into a few hiccups during the rest of the match.It was a match of runs which put us in a fifth set.For lack of better words, we crippled across the finish line with a win.Not the path we wished to take for this match, but the overarching win was our ultimate goal.That night, we traveled a little way and stopped at an IHOP for a late dinner (coach enjoyed some pumpkin spice pancakes…happy fall!) and arrived at our hotel for the weekend.I!m pretty sure we live in hotels during season and this one was our favorite so far!We hit the hay to rest up for our Friday morning surprise adventure.In the morning, we headed out to Fort Prickett and had the opportunity to learn a little bit about families that lived in WV in the 1700's.We spent time listening to stories of the Prickett family, listening to stories from our driver Tammy, and watching fabric be made by hand.It was so interesting and I kind of wished we had more time there!The scenery is beautiful, and history is one of my favorite things.Later that day we headed to David & Elkins for our second match of the weekend.The match went very well for us, a great improvement of play on our behalf from the night before.We figured out some focus and intensity problems we had the night before.We finished the match 3-0 in sets.After the match, Davis & Elkins generously gave us some leftover food they had from their pre-game grill out which we gratefully took!We!re weren!t going to have enough time to make it to the restaurant we were planning on going to.God is good, and Davis & Elkins was kind enough to provide!We then traveled back to our hotel to get some rest for Saturday!smatch against Ohio Valley.We woke up ready to play and finish off the weekend with another win.We headed to the school in the morning and arrived and warmed up well in a difficult gym (low ceilings) to play.Ohio Valley gave us a great match!It was tight each set, yet we squeaked out a 3-0 win in the end.This brand new OVU team showed up to play and we learned some more of our weaknesses on the court in turn.But, all in all, we came off the weekend with three wins.Something that is difficult to do! It!s very tiring but the team didn!t crash until we got on the bus to come back home!That was our Fall Break in WV!We are excited for a HUGE week of play as we clinched a spot in the G-MAC tourney with our wins, we look forward to playing for seeding.Thanks for reading!Please continue to pray for the team to find time to rest physically as well as rest in the Lord this week!!We are thankful for you!
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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.838 | 0.680 |
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".