Bibliographic record
Abstract
Executive Summary Archival institutions such as Museums of Natural History are repositories for importantrecords of elements of natural history landscapes over a geographic range and over time. The Mollusca collection of the Nova Scotia Museum is one example of where early (19thcentury) provincial collections have been documented and supplemented by further workover the following 143 years. Contemporary field investigations by the Nova ScotiaMuseum and agencies such as the Nova Scotia Department of Natural Resources haveallowed for a systematic documentation of the distribution of a selected group, thefreshwater mussels, in large portions of the province. Although this group comprises only 10 extant and one regionally-extirpated species,these collections represent important species which have been recognized as sensitiveindicators of envirorunental modification as well as larger scale climatic change. A consolidation of these data (1083 specimen lots), including 164 collections from otherNorth American and European sites allows a clear definition of baseline distributions,primarily in the 20th and beginning of the 21st century. The report summarizes collectiondata in the form of species accounts, supplemented by distribution maps, as well asspecific biological information (in a Nova Scotia context) including the requirement for afish host during early development; a further limitation on their ability to expand ranges. A selected suite of data fields for each documented collection of freshwater mussels inthe Collection of the Nova Scotia Museum is appended. Recommendations are made for future work. _____________________________________________________________________ Please note: This resource is presented as originally published. The content of older reports may not reflect the current state of knowledge on the topic documented. Please be aware of this when using this resource.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.021 | 0.007 |
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".