“Codex canadiensis”, an early illustrated manuscript of Canadian natural history
Bibliographic record
Abstract
ABSTRACT: “Codex canadiensis” consists of 79 leaves with 180 illustrations of plants, birds, mammals, fishes, and a few fabulous animals. This manuscript arguably is the most obscure and enigmatic surviving document pertaining to the early natural history of French Canada. It was lost until 1930, when Baron Marc de Villiers first published a facsimile. Two inferior editions later appeared in Canada. The codex was acquired about 1949 by Oklahoma oil baron Thomas Gilcrease and then deposited in the Gilcrease Museum, Tulsa, Oklahoma. Under the direction of one of us (Gagnon), French-Canadian scholars have established the codex's author was Father Louis Nicolas (1634–c. 1678), a Jesuit priest who laboured among tribes along the St Lawrence River and the Great Lakes during 1664–1675. This rejects the previous attribution to Charles Bécard (correctly Bécart), Sieur de Granville. The codex likely was completed in part, if not entirely, after Nicolas' return to France in 1675, and it is closely related to a much larger undated work by Nicolas, “Histoire naturelle des Indes Occidentales”. “Codex canadiensis” is among the most valuable extant manuscripts illustrating the natural history of North America as explored by early European naturalists.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.034 | 0.004 |
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".