ILD Software and Analysis Meeting
Bibliographic record
Abstract
Topic: ILD Analysis/Software \nDate: Wednesday, 8 February 2012 \nTime: 13:00, GMT Time (London, GMT) \nMeeting Number: 757 442 172 \nMeeting Password: ild \n\n\n------------------------------------------------------- \nTo join the online meeting (Now from mobile devices!) \n------------------------------------------------------- \n1. Go to https://ilc.webex.com/ilc/j.php?ED=161545967&UID=0&PW=NOTVlNDY5NTc1&RT=MTgjMjE%3D \n2. If requested, enter your name and email address. \n3. If a password is required, enter the meeting password: ild \n4. Click "Join". \n\nTo view in other time zones or languages, please click the link: \nhttps://ilc.webex.com/ilc/j.php?ED=161545967&UID=0&PW=NOTVlNDY5NTc1&ORT=MTgjMjE%3D \n\n------------------------------------------------------- \nTo join the audio conference only \n------------------------------------------------------- \nTo receive a call back, provide your phone number when you join the meeting, or call the number below and enter the access code. \nCall-in toll-free number (US/Canada): 1-877-668-4490 \nCall-in toll number (US/Canada): 1-408-792-6300 \nGlobal call-in numbers: https://ilc.webex.com/ilc/globalcallin.php?serviceType=MC&ED=161545967&tollFree=1 \nToll-free dialing restrictions: http://www.webex.com/pdf/tollfree_restrictions.pdf \n\nAccess code:757 442 172 \n
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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 | 0.010 | 0.042 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.654 | 0.710 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".