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
It is customary in contemporary design for fatigue resistance of bolted connections to use slip-critical joints. However, many existing bridges are more likely to have bearing-type joints that use either rivets or high-strength bolts. Moreover, in many of these cases, hole patterns are staggered. Fatigue fracture of tension members with bearing-type joints that use staggered holes is observed to take place on a plane perpendicular to the axis of the member. The s2/4g rule, commonly used for static strength design of bolted tension members, is not applicable for this case, and current design rules do not make it clear just what net section is to be used to calculate the stress range. The fatigue resistance of bearing-type shear splices was investigated to assess the effect of bolt-hole stagger and gauge distance on fatigue resistance. Thirty-one symmetrical bearing-type shear splices were tested at different stress ranges. Staggers varying from zero to 75mm were investigated on four sets of three specimens, and two gauge dimensions were investigated at two stress range levels. The test results indicated that neither the stagger nor the gauge dimension significantly influenced the fatigue life. An analysis of the test results indicated that none of the commonly used cross-sectional area definitions is adequate for stress range calculations. An approach that accounts for stress concentration in the calculation of the effective stress range is proposed. This approach multiplies the gross cross-section stress range by a correction factor determined using finite-element analysis. Design recommendations include a fatigue resistance curve with a slope of 7.0 and stress correction factors for the most common flat plate geometries. The proposed approach was validated using test results of other researchers on flat plates and built-up sections.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 it