Bibliographic record
Abstract
It is difficult to know where our ideas begin.It is difficult to identify the contributions of friends, family, collaborators and mentors in any singular form.This makes the experience of writing and designing dense and complicated, but also an easy and delightful place to get lost.And when you endeavour, so willfully, to lose your way, it is best to have good company.I have been veryfortunate in this regard.There are many thanks to many people, but I'll start with these important ones.To Véronique Couillard, I cannot quantify the generosity, nor describe the humor, that has kept me buoyant for so many years.Our lives have straddled many categories together, and I am so very glad she is always up for a new adventure, especially the one that has involved our son Arlo.His lightness is always uplifting, and I would like to offer a particular thanks for how he finds such laughter in "…les escaliers qui va nuls-part!"For my parents, Dennis and Sandra, support is hardly an adequate word to describe their unflinching kindness, and my brother, Deryk, for his reassuring perspectives.I learned how to ask questions amongst this family, for better or worse it is deep in my bones and leads me to many interesting places.To my extended family, the Couillards, I thank them for their incredible hearts.In particular, my sister and friend, Geneviève Couillard and her son Maxime, deserve my most gracious thanks for caring for me and Véronique and Arlo throughout this adventure.vi To everyone involved with Artengine, and in particular Remco Volmer for the many conversation and for all of the support in this expansion of endeavours.To my friend and collaborator Jessie Fyfe-Loose, who is here in between life and the life of school, I thank her for teaching me about new ways to question the world and for questioning the world with me.I will always try to go forward with grace and openness.To all my fellow students, who shared all of the layers of an architectural education.Specifically, Kyle
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.078 | 0.027 |
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".