Bibliographic record
Abstract
A Monte Carlo simulation program was used in this study to evaluate the performance of No.2 and better grade combination of 38 mm x 140 mm Western Hemlock lumber proof loaded in bending. Two proof load magnitudes of 19.54 MPa and 23.05 MPa representing the 2nd and 5th percentile load levels of the short-term strength respectively were selected for the proof testing program to investigate the impact of proof loading. The rate of loading for all the testing programs was 2679 MPa/hr. The Canadian damage accumulation model was incorporated into the simulation program to calculate the probability and time-of-failure of every member as well as the strength of the survivors after testing at the two proof load magnitudes. Damage accumulated in a member was quantified based on the strength of the weak survivors. It was found that damage accumulated appears to be greater in the weaker survived members tested at the 2nd percentile load level compare to the weaker survivors tested at the 5th percentile load level. Forty pieces of the 2000 members tested at the 2nd percentile load level broke during proof loading whereas 101 pieces failed when the 2000 members were proof loaded at the 5th percentile load level. Plots of cumulative probability distributions indicated no significant difference between the original short-term strength and the strength of the survivors tested at both proof load levels. However, approximately 11% damage was accumulated in the weakest survived members proof loaded at the 2nd percentile proof load level compared to a damage level of 1.2% experienced by the weakest survived member proof loaded at the 5th percentile load level. It appears damage did not accumulate in the survivors with bending strength values beyond 20.69 MPa and 24.48 MPa for the 2nd and 5th percentile proof load levels respectively. Therefore, when a proof load magnitude of 23.05 MPa is selected to evaluate the performance of 38 mm x 140 mm Western Hemlock lumber in bending, more reliable survivors may be obtained compare to a proof load magnitude of 19.54 MPa.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".