Mohair Fiber: Sustainability Starts at the Farm-Know your Fashion; Know Where it Comes from
Bibliographic record
Abstract
Trends in Textile Engineering & Fashion Technology Mohair Fiber: Sustainability Starts at the Farm-Know your Fashion; Know Where it Comes from Weiss Marcia1, Faust Marie-Eve2, Bellemare Jocelyn3* and Fontaine Richard4 1Department of Textile Design, Thomas Jefferson University, MFA in Fibers, Savannah College of Art & Design (SCAD), USA 2Department of Strategy, Social and Environmental Responsibility, School of Business and Management (ESG), Université du Québec à Montréal (UQAM), Canada 3Department of Analytics, Operations, and Information Technology, School of Business and Management (ESG), Université du Québec à Montréal (UQAM), Canada 4Department of Accounting, School of Business and Management (ESG), Université du Québec à Montréal (UQAM), Canada *Corresponding author:Bellemare Jocelyn, Department of Analytics, Operations, and Information Technology, School of Business and Management (ESG), Université du Québec à Montréal (UQAM), Canada Submission: August 16, 2023; Published: September 05, 2023 DOI: 10.31031/TTEFT.2023.09.000706 ISSN 2578-0271 Volume9 Issue2
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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; both teacher heads agree on what is shown here.
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".