Bibliographic record
Abstract
C.I.M is on-line. This issue marks the beginning of a new phase of publication for the journal: CIM is now available only on-line. Over its 30 year existence, CIM has been published in several formats and by different agencies. In recent years, CIM was owned and published by CMA as one of its associate journals. In 2004, CSCI purchased CIM and ownership reverted to the society. Since then, CIM has been type-set and formatted in-house and printed and distributed by University of Toronto Press (UTP) and, as in interim measure, the journal was available on the CSCI web-site. This process was threatened by the sale of UTP's off-set Printing Division. Links have now been established between CSCI, CIM and the University of Toronto Library to make use of the U of T Open Journal Access initiative to develop sophisticated on-line distribution. The Library supports journals via the Open Journal System (OJS) management software as well as providing archiving facilities. CIM will remain a subscription journal but, in the spirit of open access, all content will be freely available after a six month publication delay. Access will also be made available to all Canadian Universities via their library websites and authors will have immediate access for submitted articles.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.939 | 0.938 |
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".