Ovid MEDLINE Instruction can be Evaluated Using a Validated Search Assessment Tool
Bibliographic record
Abstract
Objective – To determine the construct validity of a search assessment instrument that is used to evaluate search strategies in Ovid MEDLINE. Design – Cross-sectional, cohort study. Setting – The Academic Medical Center of the University of Michigan. Subjects – All 22 first-year residents in the Department of Pediatrics in 2004 (cohort 1); 10 senior pediatric residents in 2005 (cohort 2); and 9 faculty members who taught evidence based medicine (EBM) and published on EBM topics. Methods – Two methods were employed to determine whether the University of Michigan MEDLINE Search Assessment Instrument (UMMSA) could show differences between searchers’ construction of a MEDLINE search strategy. The first method tested the search skills of all 22 incoming pediatrics residents (cohort 1) after they received MEDLINE training in 2004, and again upon graduation in 2007. Only 15 of these residents were tested upon graduation; seven were either no longer in the residency program, or had quickly left the institution after graduation. The search test asked study participants to read a clinical scenario, identify the search question in the scenario, and perform an Ovid MEDLINE search. Two librarians scored the blinded search strategies. The second method compared the scores of the 22 residents with the scores of ten senior residents (cohort 2) and nine faculty volunteers. Unlike the first cohort, the ten senior residents had not received any MEDLINE training. The faculty members’ search strategies were used as the gold standard comparison for scoring the search skills of the two cohorts. Main Results – The search strategy scores of the 22 first-year residents, who received training, improved from 2004 to 2007 (mean improvement: 51.7 to 78.7; t(14)=5.43, P
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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 | 0.058 | 0.331 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.014 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".