Bibliographic record
Abstract
InstituteOberwolfach in February 2003.The Oberwolfach conferences are one-week workshops with a series of presentations and, according to the custom of the Mathematical Research Institute, extensive time allocated for scientific discussions.The topics discussed at the conference included statistical population genetics, novel approaches for positional gene identification, statistical modelling of multiple disease loci, haplotype estimation and haplotype association analysis, novel designs for nuclear family studies, whole genome analysis and analysis of large pedigrees.43 colleagues from Canada, France, Germany, Great Britain and the USA participated.During the five days of the conference, 29 talks and a tutorial on variance component methods were given.We would like to thank the Mathematical Research Institute Oberwolfach for the opportunity to hold this meeting, for free accomodation, and for wonderful hospitality.The well-known 'Oberwolfach atmosphere' of the institute and the spectacular surroundings of the Black Forest, which we explored (in the snow) in the traditional Wednesday afternoon excursion, provided an ideal setting for scientific exchange.We would also like to thank Prof.
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 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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.547 | 0.354 |
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".