What do changes in inflammatory bowel disease management mean for our patients?
Bibliographic record
Abstract
Treatment goals in Crohn's disease are evolving beyond the control of symptoms. A treat-to-target approach to management that features earlier initiation of TNF antagonist therapy will enable resolution of objective parameters of inflammation. The decision to initiate anti-TNF therapy should be based on a patient-specific assessment of risks and benefits. This paradigm necessitates a complex process, influenced by multiple factors that include the quality of data available, physicians' and patients' knowledge of the data, and the preferences and values of patients, physicians and society. The potential 'opportunity cost' resulting from a delay in initiation of effective therapy, a consideration that has been neglected in the past, must also enter into the equation. Our evolving approach to the management of Crohn's disease challenges patients to participate in the decision-making process and to become an active partner in their care. Ideally, this evolution should occur within the context of an enduring physician/patient relationship that is based on mutual trust. Motivational communication provides a useful technique to improve dialogue and collaboration between healthcare professionals and patients, and may help to engage and motivate patients to commit to managing their disease.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".