Supplemental data from: Nature or nurture: A genetic basis for the behavioral selection of depth in siscowet and lean lake charr (Salvelinus namaycush) ecomorphs
Bibliographic record
Abstract
These files contain the raw depth and temperature sensor data from siscowet and lean lake charr (Salvelinus namaycush) ecomorphs tagged with pop-up satellite archival tags (PSATs). These fish were produced from wild gametes taken from Lake Superior and reared in a common garden study for nine years and then tagged with PSATs and released in southern Lake Superior. The dataset is supplemental to: Goetz, F., Sitar, S., Seider, M., and Jasonowicz, A. 2022. Nature or nurture: A genetic basis for the behavioral selection of depth in siscowet and lean lake charr (Salvelinus namaycush) ecomorphs. Canadian Journal of Fisheries and Aquatic Sciences. (in press). Data description for metadata.csv: This file contains the metadata associated with each tag deployment. This includes biological data as well as key mission paramters. Column Type Description mission_id integer mission identifier tag_sn integer tag serial number ecotype string lake trout ecotype release_date string date of tag release length_mm float total length in mm weight_g float weight in g lipid float lipid level meadured by Distell fatmeter set in research mode release_site string release site (deep or shallow site) sampling_rate string sampling interval of tag (format=HH:MM:SS) mission_end_utc datetime programmed tag pop off date and time in UTC time (format=YYYY-MM-DD HH:MM:SS) notes string notes and comments Data description for the raw sensor data files: The raw sensor data is found in the files that are prefixed with "raw-sensor-data". The data for each tag is in contained in a seperate file and the files are named as follows "raw-sensor-data-{mission_identifier}-{tag_serial_number}.csv". Column Type Description mission_id integer mission identifier tag_sn integer tag serial number timestamp_utc datetime timestamp of sensor reading (format=YYYY-MM-DD HH:MM:SS) depth_m string depth in meters temperature_c string temperature in degrees celcius
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.
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 | 0.006 |
| 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 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.448 | 0.121 |
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".