Bibliographic record
Abstract
DEPARTMENTS AND COLUMNS AT DEADLINE EDITORIAL 5 CORPORATE PROFILE 7 CORNER ON THE MARKET 8 CLOSE UP 9 COMPUTERS/SOFTWARE1 0 MANAGING12 LAW 13 GETTING ORGANIZED I4 LIST: PROPERTY MANAGEMENT FIRMS 22 LIST: MAJOR OFFICE COMPLEX LEASING GUIDE 26, 27 I 28 LIST: MORTGAGE LENDERS30 LIST: COMMERCIAL REAL ESTATE BROKERS 34 I 38 LIST: COMMERCIAL BUILDING DEVELOPERS 36 I 37 LIST: FASTEST-GROWING COMPANIES 38 WINE REVIEW 42 EXECUTIVE TIME OUT 46 RESTAURANT REVIEW 48 MANAGER'S BOOKSHELF 49 RESOURCE DIRECTORY 54 DUFF I PHELPS, LLC STOCK SHEET 55 CALENDAR 58 NEWS AND FEATURES CALIFORNIA SALARY INCREASES AT AN EIGHT-YEAR HIGH 15 GIFT GIVING AT THE HOLIDAYS 15 MANAGING "GENERATION X" WORKERS 20 LEGISLATIVE UPDATE-STATE OF CALIFORNIA. 21 FINAL AB 60 RULES ADOPTED . 23 NEW WEB SITE ATIACKS AND CONQUERS WORKPLACE DEMONS 24 THE NEW WORLD OF THE OLDER WORKER 29 NOVEMBER 2000-SLAVERY ABOLISHED IN U.S. COMPANIES! 31 FEAR RUNS RAMPANT IN MOST WORKPLACES! 33 THREE CHC INSTRUCTORS ATIEND SCIENCE SYMPOSIUM AT LAWRENCE LIVERMORE NATIONAL LABORATORY 35 CRANIAMANIA IS THE FIRST ONLINE ACADEMIC COMPETITION SITE35 VIRTUAL HI-TECH HIGH SCHOOL PROGRAM IS LAUNCHED 37 BUSINESS LEADERS GATHER TO BENEFIT INLAND EMPIRE KIDS 39 MERV KIRSHNER RETURNS TO COLLIERS SEEl-EY 40 MASTER DISTRIBUTION CENTER ADDS TO INDUSTRIAL CONSTRUCTION IN ONTARIO 40 • CITATION'S FEATURES MOUNTAIN SHADOWS AND SYCAMORE HIGHLANDS DEVELOPMENTS. 41
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.739 | 0.701 |
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; the direct Gemma label and the distilled Codex classifier 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".