The San Francisco Centralized Intake Unit: A Description of Participants and Service Episodes
Bibliographic record
Abstract
Using client data from the publicly-funded drug abuse treatment system in San Francisco, California, this study compared demographic characteristics of clients of a central intake unit (CIU) to those of clients who did not access the CIU, and examined characteristics of CIU episodes. The San Francisco CIU was intended to make appropriate referrals of CIU clients to treatment programs, and 47.9% of these episodes were followed by a subsequent treatment episode within 90-days of admission to the CIU. Of all individuals in the treatment system, a quarter had been to the CIU and as many as 9% of all treatment episodes were at the CIU. The majority of CIU episodes were short, consistent with the nature of assessment and referral services. These data suggest that incorporating strategies to enhance admissions to post-CIU services could increase CIU impacts. The post-CIU admission patterns were consistent with greater availability of outpatient and day treatment slots in the system. The pre-CIU admission patterns suggested that treatment agencies in the system used the CIU as a means to transition their clients into additional or longer-term treatment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".