An Interprofessional Approach to Improve Gestational Outcomes
Bibliographic record
Abstract
Sixty percent of obese women exceed the recommended criteria for gestational weight gain during pregnancy, potentially compromising optimal fetal growth. Pregnancy represents a unique period of time conducive to lifestyle modification during which we can provide patients with health advice and education; provision of information alone, however is insufficient for long‐term behavior changes. “My Clinic” is an Interprofessional clinic for pregnant women with BMI>;35 developed to improve health outcomes through lifestyle changes. Effective low cost behavior tools that promote healthy lifestyles are needed to focus clinical interventions. The purpose of this study is to assist pregnant women referred to “My Clinic” achieve a healthy pregnancy. Participants will be provided with a series of computer or paper‐based modules aimed at improving their physical activity levels and eating habits. Individually tailored modules include the following topics: time management, goal setting, action planning, self‐talk and overcoming barriers. We predict that participants undergoing specialized care and completing the modules will show increased self‐efficacy and action planning for physical activity and healthy eating, preventing excessive gestational weight gain compared to women receiving standard care in this novel study. Grant Funding Source : Departmental
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".