Bibliographic record
Abstract
This list updates the fossil fish types deposited in the collections of the University of Alberta Laboratory for Vertebrate Palaeontology (UALVP). This collection contains 111 fish holotypes, 1073 fish paratypes, 62 casts of fish holotypes from other museums, and 31 casts of fish paratypes from other museums. The catalogue number, the latest classification, a short description of the material, the collector(s) of the holotype (if known), the type locality, the full citation including the pages on which it was described, tables, and listings of any figures are provided for each type specimen. As in Bruner's (2019) list, this includes unpublished “types” languishing in Ph.D. and M.Sc. theses, as these specimens are labeled in the collections as “types” on the museum labels and in the computer catalogue. Also, this type catalogue lists specimens incorrectly cited as holotypes and paratypes in the scientific literature, mistakes made in Bruner's (2019) listing, and type specimens on long term loan to the UALVP (Paleontology Collections (PAL) of the Institut Teknologi Bandung (ITB)).
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.022 | 0.030 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.249 | 0.179 |
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".