Evaluating the effectiveness of HUDs and diegetic ammo displays in first-person shooter games
Bibliographic record
Abstract
We present an experiment comparing five ammunition display methods in first-person shooter (FPS) games. These included both diegetic (in-game) and heads-up display (HUD) options. HUD displays included a bar, icons, and a counter. Diegetic displays were displayed in-game beside the player's weapon. Two diegetic displays were evaluated: a number and bullets. We compared the performance offered by each ammunition display and player preference towards each. Results indicate that the diegetic "number-in-game" display performed best both in terms of reload time and shots taken between running out of ammunition and reloading. Participants fired an average of 35% fewer shots after running out of ammo with the number-in-game display than with the worst performing display, icons-on-HUD. Reload time was also 26% faster with the number-in-game display than with icons-on-HUD. The number-in-game display was preferred by 70% of participants.
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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 | 0.000 |
| 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 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".