Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Topic: ILD Detector Optimization\n o discussion of optimization section in LoI\n\nDate: Wednesday, 25 February 2009\nTime: 13:00, GMT Standard Time (GMT -00:00, London)\nMeeting Number: 750 963 199\nMeeting Password: ildopt\n\nPlease click the link below to see more information, or to join the meeting.\n\n-------------------------------------------------------\nTo join the online meeting\n-------------------------------------------------------\n1. Go to https://ilc.webex.com/ilc/j.php?ED=112862432&UID=0&PW=56763aa15822503c313d\n2. Enter your name and email address.\n3. Enter the meeting password: ildopt\n4. Click "Join Now".\n\n-------------------------------------------------------\nTo join the meeting on iPhone\n-------------------------------------------------------\nGo to\nwbx://ilc.webex.com/ilc?MK=750963199&MPW=e5d2e901b4217824d1984d90dad15e1a1c7a254625fea06a0ee925c03d38c2bc\n\nDon't have the iPhone WebEx application yet?\nGo to http://itunes.apple.com/WebObjects/MZStore.woa/wa/viewSoftware?id=298844386\n\n\n-------------------------------------------------------\nTo join the teleconference only\n-------------------------------------------------------\nProvide your phone number when you join the meeting to receive a call back. Or, call the number below and\nenter the meeting number.\nCall-in toll-free number (US/Canada): 866-699-3239\nCall-in toll number (US/Canada): 1-408-792-6300\nGlobal call-in numbers: https://ilc.webex.com/ilc/globalcallin.php?serviceType=MC&ED=112862432&tollFree=1\nToll-free dialing restrictions: http://www.webex.com/pdf/tollfree_restrictions.pdf\n\n-------------------------------------------------------\nFor assistance\n-------------------------------------------------------\n1. Go to https://ilc.webex.com/ilc/mc\n2. On the left navigation bar, click "Support".\n
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.022 | 0.001 |
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 it