Bibliographic record
Abstract
he previous general update of correspondence and manuscript acquisitions appeared in Russellz n.s.24, no. 1 (summer 2004): 73-7.There are 34 entries in the correspondence listing below, covering c.zz142 items.Received in July 2006, the latest acquisition number reported is 1,506 (leaving many more to be reported in a later issue).The manuscript listing of six items brings the total to 623 entries.The latest manuscript acquisition is also 1,506.Some items were received from other institutions, to whom McMaster Library is very grateful.The following abbreviations are used: L(s).or l(s).= letters(s); P(s).or p(s).= photocopies; p.c.(s).= post card(s); Ts. = typescript; tel.= telegram.Thanks are due to Carl Spadoni, Research Collections Librarian, for pursuing many of the leads whose fruition is evident here, and to Sheila Turcon, who maintains the Russell Archives' ledger of acquisitions.
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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.012 | 0.009 |
| Insufficient payload (model declined to judge) | 0.076 | 0.012 |
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".