Bibliographic record
Abstract
New Data Shows Riverside-San\nBernardino-Ontario is a Leading\nMetropolitan Area for Exports The\nU.S. Department of Commerce’s International\nTrade Administration announced new export\ndata that shows merchandise exports from\nthe Riverside-San Bernardino-Ontario\nMetropolitan area totaled a record $9.6 billion,\nan increase of 20 percent or $1.6 billion from\n2012 to 2013. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3\nWhy It’s Important for Business Owners to\nGet Out of the Office and Participate in\nConversations Gabie Boko explains there\nare several benefits to leaving the office and\nparticipating in the impactful conversations\nconferences offer. . . . . . . . . . . . . . . . . . . . . . . . . . . . 13\nStop Chasing Clients Once and For All: A\nFive-Day Plan to Bring Them to Your\nDoorstep In Mark Satterfield’s “In the One\nWeek Marketing Plan,” he explains exactly\nhow to end this perpetual pursuit of new\nbusiness and bring high-quality prospects\nto your doorstep. . . . . . . . . . . . . . . . . . . . . . . . . . . . 14\nRestaurant Review. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5\nReal Estate Notes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5\nManagement. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6\nAccounting. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7\nInvestments and Finance. . . . . . . . . . . . . . . . . . . . . . . . . . . . 8\nNetworking. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13\nSales. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14\nComputer Column. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15\nFinancial Column. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17\nExecutive Time Out. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20\nManagement Bookshelf. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25\nNew Business Lists:\nCounty of San Bernardino. . . . . . . . . . . . . . . . . . . . . . . 29\nCounty of Riverside. . . . . . . . . . . . . . . . . . . . . . . . . . . . 29\nThe Lists:\nLong Distance Companies Serving the Inland Empire. . . 32\nInterconnect/Telecommunications Firms Serving\nthe Inland Empire. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33\nCopier, Fax and Business Equipment Retailers. . . . . . . . 34\nPrivate Aviation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
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 | 0.000 |
| 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".