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Record W7028892980

Growth, nutritional quality and hematology of Arctic charr (Salvelinus alpinus) exposed to toxaphene and tapeworm (Diphyllobothrium dendriticum) larvae

2005· article· en· W7028892980 on OpenAlexaboutno aff

Bibliographic record

VenueNSUWorks (Nova Southeastern University) · 2005
Typearticle
Languageen
FieldComputer Science
TopicHistory of Computing Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsToxapheneLarvaArcticPesticideChlordaneHematologyMuscle tissue
DOInot available

Abstract

fetched live from OpenAlex

Toxaphene, an organochlorine pesticide, is the major contaminant of Arctic charr (Salvelinus alpinus) in the Canadian Arctic. The objective of this study was to investigate the combined effects of toxaphene exposure and infection by the larval stage of the cestodeDiphyllobothrium dendriticum on fish growth, nutritional composition, and hematology. Hatchery-reared Arctic charr were subjected to one of four treatments: (1) oral administration of corn oil (control); (2) single oral dose of 10 μg/g wet wt toxaphene dissolved in corn oil; (3) exposure to 15 larval D. dendriticum; and (4) exposure to toxaphene and D. dendriticum in combination. The experiment was run for 104 days. Mean final toxaphene concentrations in charr muscle were 0.121, 0.336, 0.131 and 0.458 μg/g wet wt in each treatment group, respectively. Exposure to toxaphene and D. dendriticum decreased fish growth and condition as well muscle lipid and protein content. However, toxaphene did not increase the susceptibility of Arctic charr to parasite infection. Overall, 25 of 40 fish (62.5%) exposed to larvalD. dendriticum became infected. Parasitized charr had decreased hematocrits and increased lymphocyte: erythrocyte ratios. Although total blood cell counts were decreased in all treatments compared with controls, differential leucocyte counts were unaffected. Our results suggest that toxaphene does not moderate Arctic charr resistance toD. dendriticum and there is no contaminant-parasite interaction at environmental levels.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.725
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.239
Teacher spread0.209 · 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 designTheoretical or conceptual
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

Citations0
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueNSUWorks (Nova Southeastern University)Same topicHistory of Computing TechnologiesFrench-language works237,207