Conference on Research and Innovations in Science and Technology of Material (CRISTMAS 2023)
Bibliographic record
Abstract
École Nationale Supérieure de Chimie de Paris, ParisTech, France 13-15 December 2023 This collection focuses on the recent innovations in Materials Science and advanced characterisations methods presented at the Conference on research and Innovations in Science and Technology CRISTMAS 2023. It covers topics ranging from advances in the most critical aspects in chemistry and material fabrication of nanomaterials, to the engineering of prototype devices and systems. Editorial Board: • Anna Baldycheva, University of Exeter, UK • Pavel Ginzburg, Tel Aviv University, Israel • Alexander Gumennik, Indiana University, USA • Andrei Gorodetsky, University of Birmingham, UK Scientific and Organising Committee: Anna Baldycheva, University of Exeter, UK Andrei Gorodetsky, University of Birmingham, UK Jèrome Tignon, Sorbonne University & Ècole Normale Superieure, France Pavel Ginzburg, Tel Aviv University, Israel Alexander Gumennik, Indiana University, USA Ben Hogan, Queen’s University, Canada Iveta Steblevska, Queen’s University, Canada Hani Bahrum, Tel Aviv University, Israel
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.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".