Dominant First Quarter and Offensive Boards Lift Mustangs Past Golden Eagles 78-71
Bibliographic record
Abstract
used 12 early points from Erin Baxter to lead a dominant first quarter as the Mustangs took down the University of Minnesota Crookston women's basketball team 78-71.The Golden Eagles played even with the Mustangs in the second half.However, they would be unable to overcome the early 41-34 deficit at the half.Friday's tilt was played at the R/A Facility in Marshall, Minn.The Golden Eagles fall to 10-11 (5-10 NSIC) with Friday's loss.Southwest Minnesota State improves to 10-10 (7-8 NSIC).The Mustangs have won three of their last four games.Minnesota Crookston has won six of the last eight games in the series, despite Friday's result.Minnesota Crookston looked to Isieoma Odor (R-Sr., F/C, Bloomington, Minn.) with 25 points on 11-of-20 from the field.Odor added five boards.She has 1,388 career points in her career.Odor needs 72 points to surpass her former teammate Alexa Thielman for fourth all-time on the career scoring list.Odor scored 21 of her 25 in the second half, as she overcame a 2-of-7 start from the field, along with two early fouls.Paige Cornale (Fr., G, Oak Creek, Wis.) continued her strong play of late with a career-high 14 points.She is averaging 10.0 points per game in her last four games.Cornale shot 5-of-13 from the field, and 2-of-3 from beyond the arc.Caitlin Michaelis (Sr., G, Marshfield, Wis.) added 11 points on 4-of-6 from the field, and 2-of-4 from behind the three-point line.Kylea Praska (Fr., G, Thief River Falls, Minn.) and Kylie Post (Fr., G, Corcoran, Minn.) each added six points.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.045 | 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 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".