Analysis of Correlation Coefficients between Two Orthogonal Components of Strong-Motion Records
Bibliographic record
Abstract
我が国の原子力施設の耐震設計において応答スペクトルに基づく方法で入力地震動を作成する場合，水平成分については1つの目標応答スペクトルに対し直交する2成分の模擬地震動を作成する．その際，両者の特徴は一様乱数によって与えられた位相のランダム性や観測記録における異なる2成分の位相特性の違いによって区別されている．一方，米国の原子力規制委員会の基準では，3成分を同時入力して原子力施設等の地震応答解析を実施する場合は，入力する3成分が互いに統計的に独立であることを示すべきとされており，基準値としてChen (1975)による相関係数の絶対値を導入している．本論文では，Chen (1975)による相関係数に着目して，我が国の2000年以降の強震動加速度記録を対象に直交2成分間の相関係数を求め，統計処理を行うとともに地震に関する各種パラメータが相関係数に与える影響を分析した．また，一般的な応答スペクトルに基づく方法により模擬地震動を作成した上で相関係数を解析した．
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".