Bibliographic record
Abstract
The first step in managing a patient with constipation is to understand the precise nature of the complaint. Is the onset recent? What are the frequency and form of the stools, and how much effort is required to defecate? Is constipation steady or alternating as in irritable bowel syndrome? Are there structural, metabolic or pharmacological confounders? Is the patient depressed? Has dietary fibre been tried at a sufficient dose? What are the patient's understanding and beliefs about the symptoms? Has there been sufficient and appropriate investigation? Armed with the answers to these questions, physicians can help most patients through lifestyle, dietary and pharmacological adjustments, along with supplementary fibre. Some patients may require regular doses of an osmotic laxative. Those few that fail these measures should have their transit time estimated while on a high fibre diet; if it is normal, further testing is unlikely to help. The above efforts should be re-emphasized, and reassurance should be offered. Some patients may require a psychological assessment. If transit time is prolonged and the patient may benefit from surgery for colonic inertia or biofeedback for anismus, then colon and anorectal function should be assessed. The decision to perform further tests should be made carefully, and unrealistic expectations should be discouraged. Before surgery is offered, the patient should have the benefit of receiving an expert opinion. Biofeedback helps some patients with isolated anorectal dysfunction.
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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".