Reliability Approach to Intersection Sight Distance Design
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The intersection sight distance (ISD) design presented by AASHTO is based on extreme values of the component design variables such as design speed, perception–reaction time (a high percentile), and friction coefficient (a low percentile). A reliability method is presented, based on AASHTO, that does not rely on extreme values but instead considers the moments (mean and variance) of the probability distribution of each random variable. The method also accounts for correlations among the component random variables. In Cases I and II of AASHTO, the variations of the sight distance along both legs of the intersection are considered for both design and evaluation. For evaluation (involving an exiting obstruction), these variations are combined into a single variable that determines whether the corresponding sight line is obstructed. In Case III, only the sight distance leg along the major road has variations. The proposed method is straightforward and involves simple, closed-form mathematics for calculating sight distance and associated reliability. Sensitivity of ISD to various design variables is examined. ISD reliability-based values for various cases are presented from data reported in the literature, and results are compared with current AASHTO design values.
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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 | 0.022 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it