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
This book is the third in a series of publications that present the latest advancements in research on mass customization and personalization. Starting with Tseng & Piller (2003) and continuing with Piller, Reichwald & Tseng (2006), we again could collect the thinking of some of the leading scholars and practitioners in the field. In comparison to the previous editions, this is the most comprehensive collection of writings on mass customization ever. This inspired our publisher to name it the "Handbook of Research in Mass Customization & Personalization". The contributions in this handbook were inspired by the 4th World Conference on Mass Customization and Personalization (MCPC 2007), a biannual academic event that gathers the international research and practice community interested in mass customization, held in October 2007 at the Massachusetts Institute of Technology (MIT), hosted by the MIT Smart Customization Group (Mitchell et al. 2007). The conference also included a business seminar held at HEC Business School in Montreal, Canada. The participant roster of the conference represented the interdisciplinary nature of customization and personalization
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 | 0.003 |
| 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