Additional file 1: Table S1. of Genetic variation associated with healthy traits and environmental conditions in Vaccinium vitis-idaea
Bibliographic record
Abstract
Sampled V. vitis-idaea sites in Newfoundland and Labrador, Canada. Each site is coded by ecoregion, mean annual temperature, mean summer temperature, mean annual precipitation, mean annual runoff, surface water pH, surface water sensitivity to acid rain, and proximity to the coast (Government of Newfoundland and Labrador 1992, and Alam et al. 2016). Table S2. Number of methods (LFMM, SamBada and Chi^2) that predicted a significant association (p < 0.01) between each SNP and biochemical/environmental variable. SNPs are the ones inferred to be significantly associated with a variable by at least two methods. Table S3. Number of SNPs in common between each pair of biochemical/environmental variables. Only SNPs inferred to be significantly associated with at least one variable by at least two methods are considered. Table S4. Moran.I test results per variable. Table S5. Data visualized in Fig. 4 Top. Table S6. Data visualized in Fig. 4 Bottom. (XLS 62 kb)
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.455 | 0.079 |
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".