Bibliographic record
Abstract
DEPARTMENTS AND COLUMNS\nAT DEADLINE\nCOMMENTARY\nGETTING ORGANIZED\nCORPORATE PROFILE\nCORNER ON THE MARKET\nCLOSE UP\nCOMPUTERS/SOFTWARE\nEMPLOYERS GROUP\nMANAGING\nLAW\nLIST: ENIVORNMENTAL COMPANIES\nLIST: SUBSTANCE ABUSE PROGRAMS\nLIST: I.E. LARGEST EMPLOYERS\nDUFF & PHELPS, LLCC STOCK SHEET\nLIST: MBA/ EXCECUTIVE PROGRAMS\nDESERT BUSINESS JOURNAL\nSTATLER'S BEST BET$\nEXECUTIVE TIME OUT\nMANAGER'S Bookshelf\nWINE REVIEW\nRESTAURANT REVIEW\nRESOURCE DIRECTORY\nCALENDAR\nNEWS AND FEATURES\nThe Business of Clean Air .............................................................. 4\nParis L.A. Catering ... Bringing European Charm to the I. E ............ 16\nCaterers Cook up Festive Fare in the Inland Empire .................... 17\nCommunity Bancorp Second Quarter Profits Up 21 Percent; Enters\nNext Phase of SBA Retention Strategy ..................................... 19\nA Common Sense Approach to Environmental Cleanups .............. 23\nLack of Product Creates a Tightening Multi Housing Market ....... 25\nBoard Chairman Focuses on Community Health .......................... 27\nThe Community of Riverside Teaching and Education\nCollaborative ...................................................................... 29\nHospital Opens $8.6 Million Cardiac Catheterization Lab ............ 30\nTemps Plus, Inc. Celebrates 5th Anniversary ............................... 32\nSpecialized Temporary Services- Finding the Firm That Will Work\nfor You .................................................................................... 35\nUnstable Economy Means Mounting Pressure in the Workplace .. 37\nCoca-Cola Foundation Gives College Students "The Real Thing" .. 41\nleading Recruitment Experts Agree That E-Recruiting Is No\nPanacea ............................................................................. 43
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) | 0.002 | 0.002 |
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".