Bibliographic record
Abstract
AT DEADLINE……………........................................1 COMMENTARY…………………………………......4 EDITORIAL…………………………………………..4 CLOSE-UP……………………………………………9 COMPUTERS/SOFTWARE………………………....10 MANAGING……………………………………........12 CORPRATE PROFILE……………………………....13 GETTING ORGANIZED…………………………….14 CORNER ON THE MARKET…………………….…21 HEALTH CARE…………………………………..….22 INVESTMENT & FINANCE………………………...23 INSURANCE…………………………………………24 STALER’S BEST BETS……………………………...25 LARGEST CREDIT UNIONS LIST…………………26 BANKING…………………………………………….27 DESERT JOURNAL………………………………….31 LAW…………………………………………………..32 LAW FIRMS LIST……………………………………33, 34 SECOND PAGE………………………………………36 WINE REVIEW……………………………………….37 EMPLOYER ISSUES…………………………………38 RESTAURANT REVIEW…………………………….40 EMPLYMENT SERVICES/AGENCIES LIST…….....42-44 MANAGERS BOOKSHELF………………………….45 NEW BUSINESSES…………………………………..49-51 RESORUCE DIRECTIVE……………….....................53, 54 EXECUTIVE TIME OUT……………………………..55 WEATHER INFORMATION………………………………...1 AGUA CALIENTE BAND DONATES MORE THAN $1 MILLION……1 “THE FRANKEN SISTERS”………………………………….1 FORD FOUNDATION GRANT……………………………….4 TOP FIVE WAYS TO OPTIMIZE STAFFING……………….5 LARRY MARINO’S: “MODERN TOWN HALL”……………7 PROPOSED BUDGET CUTS, ARC RIVERSIDE…………….20 LOCAL MARKETING COMPANY EARNS AWARDS……..21 BUSINESS ETIQUETTE FOR THE 2000s!...............................25 M.B.A. STUDENTS TAKE HONORS…………………………30 DIANA MARTINEZ NAMED PRESIDENT OF BIA, DESERT CHAPTER…………………………………………...31 ONTARIO COMPLETES AIR CARGO STUDY……………..36 OLIVE GARDEN’S CULINARY LEADERS…………………36 FACES IN BUSINESS………………………………………....39
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.063 | 0.020 |
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".