Thomas P. WilcoxCharacterization and Evolution of Peridinin-Chlorophyll a Binding Protein Gene Families in Symbiotic Dinoflagellates
Bibliographic record
Abstract
To all my family members present and past who encouraged and supported me emotionally, helped me financially and kept doing so through all seasons long after they ceased to understand what I was working on. And especially to the three women who have had the largest positive impacts on my life, my mother Ann, my wife Melada and my daughter Lauren. Acknowledgements Substantial help with this work in the form of molecular training and critical feedback came from Dr. Peter Vize of the University of Calgary and Dr. Thomas Wilcox of the University of Texas at Austin. Thanks to Dr. Robert Trench formerly of UC Santa Barbara for donation of Symbiodinium cultures and exchange of ideas. Dr. Eric Lader at Ambion, Inc. provided access to an ABI 7700 and provided valuable assistance with the quantitative real-time PCR experiments. Thanks to Drs. Bassett Maguire and Judy Lang for supervision in the early days when I was trying to figure out what I wanted to work on, and for getting me down on the reefs in the Bahamas where I could really clear my head and think. Paul Thompson and Walter Hokanson from the UT Austin found
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".