EWSLETTER ONTARIO AssociATION oF PHYsics TEACHERS (an affiliate ofthe American Association ofPhysics Teachers) Volume XVI, Number 2 Winter 1994 From the President
Bibliographic record
Abstract
Your OAPT membership allows you to provide the executive with valuable input. Any suggestions, questions on current OAPT practices, constructive criticism, etc., are always welcome. As we all tell our students: "If you have a thought, odds are a couple of others have the same thought and everyone will benefit from hearing it." There is also another avenue for supplying input to the OAPT and that is to take a position on the executive. Geographical separation is not a factor when communication is largely done via phone, fax and mail. The time commitment is not a great one. No one has extra time they need to fill up, but setting aside a few hours a month is a worthy sacrifice if you are serious about sharing physics education ideas. You can also do a presentation (short or long) at the annual conference, you can write to Paul at the newsletter or submit articles on demonstrations to Ernie at the Demonstration Comer. We want to hear from you. As you may have heard me say during the OAPT Conference at Trent University: "This is your association, help us give you what you want." I look forward to seeing you all in Ottawa next
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.467 | 0.196 |
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".