Research on the impact of momentum based on quantitative models
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
Momentum is a concept that plays an important part in the game but is difficult to quantify. In order to understand the impact of momentum on sports competitions, in this paper we examine this topic in depth and closely from multiple perspectives and levels. We first analyzed the various factors affecting the momentum, judged the significant degree of the influence of the base score, the hold score, the break score, and the consecutive score rewards on the match, and gave different scores according to the magnitude of the influence. Then we categorize match features into basic features and advanced features. In addition, we analyze the features that should be supplemented in the prediction model for the same sport in different kinds of matches as well as in diverse middle sports, and extend and adjust the model according to their special characteristics. Finally, we summarize the advantages and disadvantages of the model and systematically report the overall ideas and consequences of our thesis in the form of a memo.
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 | 0.000 |
| 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) | 0.000 | 0.000 |
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