Bibliographic record
Abstract
OBJECTIVE: Because data published on waiting times are largely determined from questionnaire-type surveys, which generate inconclusive opinion-based results, the objective of this study was to provide a quantitative measure of the extent and variance of waiting times among 3 elective general surgery procedures DESIGN: A prospective case study. SETTING: The Royal Alexandra Hospital, Edmonton. PATIENTS: From Feb. 1 to Mar. 15, 1999, all cases (90 patients) for each designated procedure--open or laparoscopic cholecystectomv for biliary colic or cholelithiasis, segmental resection or modified radical mastectomy for breast carcinoma and colon or rectal resection for colorectal carcinoma--were tabulated daily from the hospital elective operating lists. Data were prospectively acquired from individual surgeon offices (11 surgeons). Sixteen of the 90 patients were excluded, leaving 74 for analysis. OUTCOME MEASURES: Time in days from initial referral by the general practitioner to the surgeon (T1), time in days from the initial visit with the surgeon to operation for patients requiring no further diagnostic work-up by the surgeon (T2A), and time in days from the initial visit with the surgeon to operation for patients requiring further diagnostic work-up (T2B). RESULTS: The waiting period for patients who underwent non-cancer-related procedures (cholecystectomy) ranged from 83 to 106 days; patients with breast cancer waited an average of 24 (T1 + T2A) to 66 (T1 + T2B) days from the day of referral to the date of surgery and those with colorectal cancer waited an average of 32 (T1 + T2A) to 51 (T1 + T2B) days from the time of referral to operation (p < 0.05). CONCLUSION: This preliminary report aimed at quantitative measurement of time spent waiting for elective general surgery indicates that patients who underwent non-cancer-related procedures waited significantly longer for their surgery than patients who required procedures for cancer.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".