RAPHIDOPHYCEAE [CHADEFAUD EX SILVA] SYSTEMATICS AND RAPID IDENTIFICATION: SEQUENCE ANALYSES AND REAL‐TIME PCR ASSAYS<sup>1</sup>
Bibliographic record
Abstract
Species within the class Raphidophyceae were associated with fish kill events in Japanese, European, Canadian, and U.S. coastal waters. Fish mortality was attributable to gill damage with exposure to reactive oxygen species (peroxide, superoxide, and hydroxide radicals), neurotoxins, physical clogging, and hemolytic substances. Morphological identification of these organisms in environmental water samples is difficult, particularly when fixatives are used. Because of this difficulty and the continued global emergence of these species in coastal estuarine waters, we initiated the development and validation of a suite of real-time polymerase chain reaction (PCR) assays. Sequencing was used to generate complete data sets for nuclear encoded small-subunit ribosomal RNA (SSU rRNA; 18S); internal transcribed spacers 1 and 2, 5.8S; and plastid encoded SSU rRNA (16S) for confirmed raphidophyte cultures from various geographic locations. Sequences for several Chattonella species (C. antiqua, C. marina, C. ovata, C. subsalsa, and C. verruculosa), Heterosigma akashiwo, and Fibrocapsa japonica were generated and used to design rapid and specific PCR assays for several species including C. verruculosa Hara et Chihara, C. subsalsa Biecheler, the complex comprised of C. marina Hara et Chihara, C. antiqua Ono and C. ovata, H. akashiwo Ono, and F. japonica Toriumi et Takano using appropriate loci. With this comprehensive data set, we were also able to perform phylogenetic analyses to determine the relationship between these species.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".