Bibliographic record
Abstract
Low back pain (LBP) dan depresi sama-sama merupakan masalah kesehatan yang banyak dijumpai pada masyarakat umum yang sering terjadi pada kelompok usia produktif dengan beban kerja fisik yang berat maupun pada kelompok usia lanjut. Kedua keluhan ini , dapat saling memengaruhi dan saling memperberat. Biasanya keluhan LBP muncul lebih dulu kemudian diikuti dengan depresi. Keluhan LBP dan depresi ini sangat menggang gu produktivitas maupun aktivitas sehari-hari seseorang dan membuat biaya kesehatan menjadi besar (rata-rata meningkat 2x lipat). Di lnggris pada tahun 2003 dikatakan ting kat absensi dan tuntutan/klaim di bidang kesehatan akibat depresi meningkat tajam dan menjadi permasalahan besar bagi ilmu kesehatan masyarakat dan ekonomi. Penelitian Caroll dkk dari Universitas Alberta, Kanada, yang dipublikasikan tahun 2004, menunjuk kan bukti bahwa depresi sebagai faktor independen dari keluhan LBP. Mengingat adanya keterkaitan-erat dan bersifat timbal balik, maka diperlukan suatu upaya penatalaksanaan yang komprehensif dan melibatkan berbagai disiplin ilmu dalam mengatasi keluhan LBP dan depresi ini.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.004 |
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".