Bibliographic record
Abstract
I.E. and Beyond Benefit From Ontario Mills\nHomeland Security\nLaw\nGetting Organized\nIn The Interest Of Woman\nFaces in Business\nClose-Up\nComputers/Software\nManaging\nCorporate Profile\nEmployers\nPlanning Center Presented Award\n“I’d Rather Die Than Give a Speech\n$100 Billion Teachers Pension Fund Acts Against Corporate Misconduct\nCorner on the Market\nLeasing, Location and Your New Business\nSecond Page 1\nDevin Holiday Guest at Montclair Chamber Golf Tournament\nARV Assisted Living Honors Vera McConnell\nHigh-Tech Entrepreneurs Get Boost From UCR Connect\nArrowhead Foundation Awards Scholarship\nVegas-Style Casino Sets Opening Date\nDistribution\nWine Review\nCalifornia’s Business Leaders Announce Proposal\nRestaurant Review\nInland Empire – First Quarter 2002\nDesert Journal\nManager’s Bookshelf\nAmerican Mortgage Networks Expands\nExecutive Time Out
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 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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; both teacher heads 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".