Bibliographic record
Abstract
Present study investigated the relationships between rationales for the result of attacks and success of attacks during attacks involve a receive, a toss and a spike. Quarter finals, semi-finals and final of All Japan Intercollegiate Volleyball Championships tournament were analyzed using mathematical Quantification Theory Type One. Main factors for the success of attacks were judgment of opponent’ s blocks and tosses. For the blocks, large positive influences on success of attack was observed when 3 players jumped to block and at least one player performed block 2 or block 3. On the other hand, large negative influences on success of attack was revealed when 3 players jumped to block and at least 2 players performed block 1. For the judgment of tosses, the largest influence on success of attack was shown by toss-A followed by toss-B and then toss-C. Moreover, it was found that players can be categorized into “reliable type player”, “constant type player”, “gamble type player” and “clunker type player” when regression coefficient calculated from mathematical Quantification Theory Type One was employed for the analysis.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".