Bibliographic record
Abstract
Key to revenue trend indicators: ◄NEUTRAL ► = Variance of-1 % to +2 % compared to projections. ▲POSITIVE ▲ = Positive variance of>+2 % compared to projections. ● WARNING ● = Negative variance of-1 % to-4 % compared to projections. ▼NEGATIVE ▼ = Negative variance of>-4 % compared to projections. 1 Q2 2010- August 17, 2010CITY FINANCIAL OVERVIEW EXECUTIVE SUMMARY General Fund revenues of $13,239,752 are $158,909 or 1.2 % above projected revenue. Sales tax, local criminal justice sales tax, and interest income revenue finished the first half below adjusted revenue. Property tax; utility tax and franchise fees; Seattle City Light contract payment; gambling tax revenue; permit revenue; recreation fees; fines and licenses; and miscellaneous revenues are all above adjusted projections. General Fund expenditures during the first quarter are $256,946 or 0.9 % below projected expenditures. Street Fund revenues total $1,186,133 and are $5,799 or 0.5 % above projected revenues. Street Fund expenditures total $1,092,499 which is $54,945 or 4.8 % below projections. The Surface Water Utility Fund (SWM) revenue collections equal $1,647,312 and are $1,583 or 0.1 % above projections. Expenditures are $1,635,288 or $314,995 or 16.2 % less than projected. Real estate excise collections totaled $490,104 which is $39,668 or 7.5 % below projections. Fuel tax collections totaled $558,745 which is $9,733 or 1.8 % above projections
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.285 | 0.227 |
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".