New Insights into Iron-Based Photosynthesis
Bibliographic record
Abstract
2478 New insights into iron-based photosynthesis KATE J. THOMPSON1, MARC LLIROS2 , CARLES M. BORREGO3,4, PAUL KENWARD1, FRANCOIS DARCHAMBEAU 5, ALBERTO V. BORGES5, DON E. CANFIELD6 AND SEAN A. CROWE1 1University of British Columbia, Canada kjtomo14@gmail.com, pkenward@eos.ubc.ca sean.crowe@ubc.ca 2Universitat Autonoma de Barcelona, Spain marc.lliros@uab.cat 3Catalan Institute for Water Research (ICRA), Spain cborrego@icra.cat 4University of Girona, Spain, carles.borrego@udg.cat 5Universite de Liege, Belgium. alberto.borges@ulg.ac.be, Francois.Darchambeau@ulg.ac.be 6University of Southern Denmark, Denmark dec@biology.sdu.dk
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".