Bibliographic record
Abstract
The CUA continues to improve on academic and administrative levels.I am proud to say that we have reached a formal agreement between the CUA and SIU -we are now equal partners in the central office in Montréal.We hope that this new arrangement will increase the efficiency of our organization and ultimately cut down on costs.We will be able to closely monitor our expenses and allot them to their appropriate divisions (Administration, Annual Meeting, Office of Education and Publications).The CUA staff will continue to respond in a timely manner to the demands of our members.Our evolution and growth is a testament to our openness to change.We have taken on a very ambitious program with the Office of Education.With the departure of Dr. Harry Zwanenburg, we are now in the process of rearranging this office and determining the specific academic and administrative needs to make it flourish.The team of hard working volunteers is putting the final touches on the Annual Meeting, in Edmonton (June 22-25, 2008).Dr. Mike and Bonnie Chetner have a fabulous social program.We are looking forward to lots of fun for those who venture out west.The academic portion of the meeting, put together by Dr. Tim Wollin and Dr
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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 | 0.016 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.015 | 0.019 |
| Insufficient payload (model declined to judge) | 0.260 | 0.185 |
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".