Editor-In-Chief for Clinical and Investigative Medicine
Bibliographic record
Abstract
The Canadian Society for Clinical Investigation (CSCI) is seeking an Editor-in-Chief for the Society’s journal, “Clinical and Investigative Medicine”. If you are knowledgeable in the areas of clinical research that span disciplines from fundamental to clinical to population health, and you are keenly interested in encouraging the careers of young investigators, this may provide an exciting opportunity. Editor-in-Chief is an important role for the Society. Clinical and Investigative Medicine (CIM) is a well-established open-access peer-reviewed journal owned by CSCI. The person selected for this role will be responsible for choosing articles based on their scientific quality and for overseeing all aspects of their review and publication. The journal focuses on clinical and research articles that provide insights into the scientific basis for clinical disease processes. The journal also actively supports the careers of young investigators and encourages publication of their work. Five-year Impact Factor: 1.32 Citations: 1,200/year History: 1978-present Published: Four times annually ISSN: 1488-2353 (electronic) NLM ID: 7804071 Indexing: Index Medicus; Medline; and PubMed; v1n1, (1978) to present. Print issues v1n1– v29n5 (2006); electronic issues v30n1–v45n1 (present) Please contact CIM Manager rob@Gallaher.ca for more information.
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 | 0.015 | 0.062 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.158 | 0.192 |
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".