Probabilistic model for cattail and canola fibers: effect of environmental conditions, structural parameters, fiber length, and estimators
Why this work is in the frame
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Bibliographic record
Abstract
Biomass fibers are being widely investigated for industrial applications as an alternative to synthetic fibers using a standard humidity condition. In this study, the mechanical properties of two waste biomass fibers – canola and cattail – have been investigated when subjected to different environmental conditions, fiber length, and type of estimators used during analysis. The effect of different environmental conditions and structural variations were investigated by measuring the tensile properties after exposing them to eight different relative humidity conditions using a fixed fiber length of 25 mm. Further investigation was conducted using fiber lengths of 25, 35 and 45 mm using the most conservative relative humidity condition. The data were analyzed by a Weibull distribution model using four different estimators. The results revealed that Weibull strength ( σ avg ) and modulus (E avg ) closely followed experimental values for cattail and canola fibers. The different relative humidity conditions and fiber lengths resulted in different Weibull parameters with 11% relative humidity and the mean rank estimator predicted the most conservative tensile strength for both waste biomass fibers. The experimental and characteristic Weibull strength decreased when fiber gauge length increased from 25 to 45 mm. The tensile strength and modulus of both waste biomass fibers at 50% reliability lie within the range of average experimental values. However, these values are reduced to 155 MPa (strength) and 20 GPa (modulus) for cattail fiber at 90% reliability. The survival probability of the tensile strength and modulus were found to be the highest at 75% and 100% relative humidity for cattail and canola fibers, respectively.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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