A theory of power laws in human reaction times: insights from an information-processing approach
Bibliographic record
Abstract
Human reaction time (RT) can be defined as the time elapsed from stimulus presentation until a reaction/response occurs (e.g., manual, verbal, saccadic, etc.). RT has been a fundamental measure of the sensory-motor latency at suprathreshold conditions for more than a century and is one of the hallmarks of human performance in everyday tasks (Luce, 1986; Meyer et al., 1988). Some examples are the measurement of RTs in sports science, driving safety or in aging. Under repeated experimental conditions the RT is not a constant value but fluctuates irregularly over time. Stochastic fluctuations of RTs are considered a benchmark for modeling neural latency mechanisms at a macroscopic scale (Luce, 1986; Smith and Ratcliff, 2004). Power-law behavior has been reported in at least three major types of experiments.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 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".