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Record W7038830829

Implementing recovery strategies for mussel species at risk in Ontario

2007· dissertation· en· W7038830829 on OpenAlexaboutno aff

Bibliographic record

VenueThe Atrium (University of Guelph) · 2007
Typedissertation
Languageen
FieldMedicine
TopicRadiation Therapy and Dosimetry
Canadian institutionsnot available
Fundersnot available
KeywordsMusselHost (biology)Abundance (ecology)JuvenilePopulationFish <Actinopterygii>Identification (biology)
DOInot available

Abstract

fetched live from OpenAlex

The identification of host fishes, elucidation of population dynamics, and determination of potential sites for reintroduction and augmentation of Species at Risk (SAR) unionid mussels are important goals of current recovery strategies. Host fishes were identified or confirmed for 'Epioblasma torulosa rangiana, Epioblasma triquetra, Lampsilis fasciola, Obovaria subrotunda, Ptychobranchus fasciolaris' and 'Villosa fablis'. Importantly, the absence of a host fish for 'E. t. rangiana' may help to explain its SAR status. Results indicated that there are systematic relationships among mussels and their host fish, that juvenile production rates differ among host fishes, and that there are site specific differences in the abundance estimates (range: 3-10974 individuals), sex ratios, proportion of gravid females (10-40%), and growth rates (0.2-0.4 cm/year) for the mussel SAR in the Sydenham River. This information is vital for understanding the biology of these organisms and in facilitating their recovery.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.571
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.022
GPT teacher head0.264
Teacher spread0.242 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2007
Admission routes1
Has abstractyes

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