# The Author(s) 2007 Dear Sirs,
Bibliographic record
Abstract
With great interest, we read the short comment of Giovanni Lucignani about infection imaging [1]. Here, commentaries are given, derived from a literature search including summaries of recently published articles. An important part of the publication was dedicated to the labelling of living bacteria with antimicrobial agents, mainly to the application of radiolabelled antibiotic ciprofloxacin for the specific detection of bacteria. Dr. Lucignani stated; “that the approach with technetium-labelled ciprofloxacin showed considerable promise in the preliminary studies but clinical trials have shown limitations”. On the contrary, most pre-clinical studies have shown poor specificity of technetium-labelled ciprofloxacin for bacterial infections [2–7] and vivid discussions related to this topic took place [8–10, 17]. One of the most tested radiolabelled ciprofloxacin is Infecton ® (Draximage, Quebec, Canada). This compound was evaluated in the International Atomic
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.105 | 0.143 |
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".