Bibliographic record
Abstract
This chapter contains sections titled: Introduction Anaerobiospirillum spp. Anaplasma phagocytophilum Arcobacter spp. Bacillus anthracis Bartonella species Bartonella henselae Bartonella clarridgeiae Bartonella vinsonii subsp. berkhoffii Bergeyella zoohelcum Bordetella bronchiseptica Brucella canis Campylobacter spp. Capnocytophaga spp. Chlamydophila felis Chlamydophila psittaci Clostridium difficile Clostridium perfringens Corynebacterium ulcerans Coxiella burnetii Edwardsiella tarda Ehrlichia canis Ehrlichia chaffeensis Ehrlichia ewingii Eikenella corrodens Enterococcus spp. Escherichia coli Francisella tularensis Helicobacter spp. Leptospira spp. Listeria monocytogenes Mycobacterium avium complex (MAC) Mycobacterium bovis Mycobacterium lepraemurium Mycobacterium marinum, Mycobacterium fortuitum, and Mycobacterium chelonae Mycobacterium tuberculosis Pasteurella multocida Plesiomonas shigelloides Rat-bite fever Rickettsia felis Rickettsia rickettsii Salmonella spp. Staphylococcus aureus Staphylococcus pseudintermedius/Staphylococcus intermedius Staphylococcus schleiferi Streptococcus canis Group A Streptococcus (GAS) Streptococcus equi subsp. equi S. equi subsp. zooepidemicus Yersinia enterocolitica Yersinia pestis Yersinia pseudotuberculosis References
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.334 | 0.235 |
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".