Archive of Morphological Data for the Coregonus artedi Species Complex of the Great Lakes, Lake Nipigon, and Great Slave Lake
Bibliographic record
Abstract
This publication is a user guide for an archive of morphological data recorded by various authors from North American ciscoes of the Coregonus artedi species complex (subfamily Coregoninae). The archive is accessible from the Great Lakes Fishery Commission’s (GLFC) server, is open access, and contains data for the Laurentian Great Lakes; Lake Nipigon, Ontario; and Great Slave Lake, Northwest Territories. The archive comprises morphometrics and meristics (together metrics) for 6,700 individual Cisco of which 1,400 are accompanied by images. In addition, the archive contains metrics presented as arrays by W. N. Koelz, Coregonid fishes of the Great Lakes, Bulletin of the U.S. Bureau of Fisheries 43(2):297-643, which were based on 10,000 individuals. Spreadsheets in the Metrics folder of the archive are divided broadly into Contemporary and Historical subfolders and the Contemporary subfolder is further divided into Cisco Monograph and Extra Monograph subfolders to encourage statistical assessment of findings in GLFC Miscellaneous Publication 2023. The Images folder is organized into subfolders by lake. Tables in this user guide allow for quick determination of the availability of data by lake, subspecies, author, and year.
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 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".