Understory kelp biomass data from BC Central Coast
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The understory kelp biomass dataset is a component of Hakai Institute’s Nearshore research and monitoring program. This dataset characterizes spatial and temporal trends in understory kelps and kelp-consuming invertebrate communities at 22 rocky bottom subtidal sites near Calvert Island on the Central Coast of British Columbia, Canada (2014-now). Data coverage varies by year. The total length and abundance of all kelps, Desmarestia species, and urchins were measured at 6 sites seasonally (5 times within a year) from 2014-2018. Urchin behaviour was also recorded. From 2016-current, additional sites (4-15) were surveyed annually using a variation on the sampling design (reduced measurements on a subset of sites). In 2018-current kelp consumer species abundance, including small mobile grazing invertebrates, were recorded. Dry weight values and length to weight relations are also provided to extrapolate density and morphology data to biomass. Spatial and temporal variability in kelp and invertebrate community relationships is described. This data package is freely available to everyone, following the principles of equitable access and benefit sharing. However, we expect all data users to give attribution to the data providers (read our data license) and the use of these data should happen in the light of fair use, i.e.: 1) respect the data providers, and provide helpful feedback on data quality, and 2) communicate and/or collaborate with the providers if you are considering using this dataset for manuscripts or other forms of reporting.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.101 |
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 it