The Process of Evidence-Based Clinical Decision Making in Occupational Therapy
Bibliographic record
Abstract
Article| Online July 01 2003 The Process of Evidence-Based Clinical Decision Making in Occupational Therapy Christopher J. Lee; Christopher J. Lee Christopher J. Lee, PhD, is Assistant Professor, School of Occupational Therapy, The University of Western Ontario, London, Ontario, N6G 1H1 Canada; cjlee@uwo.ca Search for other works by this author on: This Site PubMed Google Scholar Linda T. Miller Linda T. Miller Linda T. Miller, PhD, is Associate Professor, School of Occupational Therapy, The University of Western Ontario, London, Ontario, Canada Search for other works by this author on: This Site PubMed Google Scholar Author & Article Information Online Issn: 1943-7676 Print Issn: 0272-9490 Copyright © 2003 by the American Occupational Therapy Association, Inc.2003 The American Journal of Occupational Therapy, 2003, Vol. 57(4), 473–477. https://doi.org/10.5014/ajot.57.4.473 Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Share Icon Share Facebook Twitter LinkedIn Email Tools Icon Tools Get Permissions Cite Icon Cite Search Site Citation Christopher J. Lee, Linda T. Miller; The Process of Evidence-Based Clinical Decision Making in Occupational Therapy. Am J Occup Ther July/August 2003, Vol. 57(4), 473–477. doi: https://doi.org/10.5014/ajot.57.4.473 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search nav search search input Search input auto suggest search filter All ContentThe American Journal of Occupational Therapy Search Advanced Search AOTA Taxonomy: Evidence-Based Practice Keywords: evidence-based practice, health care decision making This content is only available via PDF. Copyright © 2003 by the American Occupational Therapy Association, Inc.2003 Article PDF first page preview Close Modal You do not currently have access to this content.
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 | 0.011 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".