Bibliographic record
Abstract
News and Features\nThe Way You Do Anything Is the Way You Do\nEverything (and Nine More “Tough Love” Truths\nfor Business Owners) Suzanne Evans says that you,\nand you alone, are the source of your success or failure.\nShe gives us 10 inconvenient but ironclad truths that\nall business owners should take to heart. . . . . . . . . . . . 9\nWill Your Social Security Check Be in the Mail\nCome 2015? Economist Allen W. Smith says there is\nno trust fund, and a number of elected officials,\nincluding former President George W. Bush, have\nacknowledged that. . . . . . . . . . . . . . . . . . . . . . . . . . . 18\nThe Last –Minute First-Quarter Save: Five Tactics\nto Help You Snatch Record Profits From the Jaws\nof Defeat If your business’s first quarter numbers\naren’t looking good, you may be tempted to throw in the\ntowel. But Suzanne Evans says there’s still time to turn\nthis ship around. Here, she shares five tactics that just\nmight salvage your bottom line. . . . . . . . . . . . . . . . . . 24\nAre You Talkin’ to Me? Understand and Adapt to\nDifferent Communication Styles Understanding the\nstyle of the person you are communicating with can\nmake the difference between getting your message\nacross and getting it across well. . . . . . . . . . . . . . . . . 26\nColumns\nReal Estate Notes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3\nComputer Column. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3\nSales. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6\nLeadership in Business. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7\nThe Lists:\nMBA/Executive Programs in the Inland Empire. . . . . . . 7\nThe Top HMOs and PPOs. . . . . . . . . . . . . . . . . . . . . . . . 11\nResidential Real Estate Brokers. . . . . . . . . . . . . . . . . . . . 14\nWomen-Owned Businesses. . . . . . . . . . . . . . . . . . . . . . . 16\nCommunication. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8\nInvestments and Finance. . . . . . . . . . . . . . . . . . . . . . . . . . . . 8\nBusiness Success. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9\nRestaurant Review. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15\nManagement. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24\nManager’s Bookshelf. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25\nCommunication in Business. . . . . . . . . . . . . . . . . . . . . . . . . . 26\nNew Business Lists:\nCounty of San Bernardino. . . . . . . . . . . . . . . . . . . . . . . 35\nCounty of Riverside. . . . . . . . . . . . . . . . . . . . . . . . . . . . 35\nExecutive Time Out. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.793 | 0.772 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".