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 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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".