Bibliographic record
Abstract
Hedrick SC, Chaney EF, Felker B et al. Effectiveness of collaborative care depression treatment in Veterans’ Affairs primary care. J Gen Int Med2003 ; 18 : 9 –16 [OpenUrl][1][CrossRef][2][PubMed][3][Web of Science][4] QUESTION: Does collaborative care compared with consult-liaison care improve depressive symptoms in people with major depression or dysthymia? Randomised controlled trial. Veterans’ Affairs primary care clinic, Seattle, USA. 354 people with major depression, dysthymia or both (Primary Care Evaluation of Mental Disorders and DSM-IV criteria). Main exclusion criteria were included being treated by a specialist or being treated for risk of suicide, acute psychosis, post-traumatic stress disorder or substance abuse. Collaborative team-led, guideline-based treatment plan with monitoring of the plan’s implementation in primary care, and patient support versus traditional psychiatric specialist consultation and … [1]: {openurl}?query=rft.jtitle%253DJournal%2Bof%2Bgeneral%2Binternal%2Bmedicine%2B%253A%2B%2Bofficial%2Bjournal%2Bof%2Bthe%2BSociety%2Bfor%2BResearch%2Band%2BEducation%2Bin%2BPrimary%2BCare%2BInternal%2BMedicine%26rft.stitle%253DJ%2BGen%2BIntern%2BMed%26rft.aulast%253DHedrick%26rft.auinit1%253DS.%2BC.%26rft.volume%253D18%26rft.issue%253D1%26rft.spage%253D9%26rft.epage%253D16%26rft.atitle%253DEffectiveness%2Bof%2Bcollaborative%2Bcare%2Bdepression%2Btreatment%2Bin%2BVeterans%2527%2BAffairs%2Bprimary%2Bcare.%26rft_id%253Dinfo%253Adoi%252F10.1046%252Fj.1525-1497.2003.11109.x%26rft_id%253Dinfo%253Apmid%252F12534758%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.1046/j.1525-1497.2003.11109.x&link_type=DOI [3]: /lookup/external-ref?access_num=12534758&link_type=MED&atom=%2Febmental%2F6%2F4%2F116.atom [4]: /lookup/external-ref?access_num=000180352600002&link_type=ISI
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 | 0.010 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.063 | 0.010 |
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".