Bibliographic record
Abstract
DEPARTMENTS AND COLUMNS\nAT DEADLI E\nCOMMENTARY\nEDUCATION\nCORNER ON THE MARKET\nCLOSE-UP\nCOMPUTERS/SOFTWARE\nMANAGING\nLAW\nGETTI G ORGANIZED\nEMPLOYERS GROUP\nCORPORATE PROFILE\nFINA CIAL\nSECOND PAGE ONE\nWINE REVIEW\nEXECUTIVE TIME OUT\nSTATLER'S BEST BETS\nRESTAURANT REVIEW\nMANAGER'S BOOKSHELF\nNEW BUSINESS\nNEWS AND FEATURES\nLa Quinta "Stakeholders" Break Ground\nConsolidating California’s Energy Bureaucracy\nFormer Capitan John Magness Adapts Pilot's Skill s\nFirst Lady invites CSUSB Professor to White House\nCSUSB Professor Edits New Journal\nFaces in Business\nCelebrating We Tip's 30th Anniversary\nOrchard's Market to Open New Location\nRosy Employment Picture for Ontario/Upland\nBuilding a Retirement nest Egg for Two\nInvestors Must Consider Options\nPrice WaterhouseCoopers Launches Campus Campaign\nGreat Hospitality Begins With a SMILE\nLessons in Etiquette\nCodding to Head Up Tournament Operations
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.036 | 0.047 |
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".