Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose The purpose of this paper is to broaden the inclusion of patent searching in information literacy instruction by extending it from chemistry and engineering into the life sciences. Design/methodology/approach Two case studies, one undergraduate and one graduate, from two Canadian universities described the addition of patent searching to information literacy instruction in genetics and biotechnology. Findings Results indicate that the integration of patents into information literacy sessions at the undergraduate and graduate levels not only enhance students' information literacy skills, but also help students learn more about the disciplines of genetics and biotechnology. Practical implications The results of this paper have practical and pedagogical implications for librarians teaching students how to use patents as a primary source of scientific information in the life sciences and may provide useful information for any librarians who wish to introduce students to patents. Originality/value While most of the literature about the integration of patent searching in information literacy instruction focuses on chemistry and engineering, this paper shows how integral patent information is to the life sciences, and how familiarity with patent searching can enhance student understanding of the scientific information environment.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.010 |
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 it