Psychological Evaluation for Images/Videos Using Large LED Display and Projection
Bibliographic record
Abstract
デジタルサイネージやプロジェクションマッピングなどのように、大画面・ディスプレイでの画像・動画の表示が普及しつつあり、各種の条件下でのLED ディスプレイとプロジェクターのいずれが優れているかの比較が重要である。 本研究では200インチLED ディスプレイと200インチスクリーンとプロジェクターを用いた2種類の表示を行う実験環境を用意し、照明有と照明無の2つの明るさ条件と、アートとテキストの2種類のコンテンツを使用し、3要因からなる計8種類の環境下で、24人の被験者を対象とした心理実験を行なった。得られた結果について5段階のスコアの平均値の比較と8条件間の多重比較を行い、アート＋消灯＋LED の条件が他よりはるかに良い結果であることが判明した。次に、より詳細な分析結果を知るために、3要因分散分析を実行し、3つの要素が互いにどのように影響するかを明らかにした。
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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 | 0.003 | 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 | 0.001 | 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".