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Record W2286798358 · doi:10.1111/jfd.12426

Field and laboratory transmission studies of haemic neoplasia in the soft‐shell clam, <i>Mya arenaria</i>, from Atlantic Canada

2015· article· en· W2286798358 on OpenAlexaffabout
Dante R. Mateo, G S MacCallum, J. Davidson

Bibliographic record

VenueJournal of Fish Diseases · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Invertebrate Ecology and Behavior
Canadian institutionsFisheries and Oceans CanadaUniversity of Prince Edward Island
Fundersnot available
KeywordsBiologyMytilusBivalviaSedimentMolluscaCondition indexFisheryZoologyEcologyVeterinary medicineAnimal science

Abstract

fetched live from OpenAlex

A two-year laboratory and field study was initiated in 2001 in response to mass mortalities associated with haemic neoplasia (HN) in 1999 in Prince Edward Island (PEI) soft-shell clams, Mya arenaria. A laboratory proximity experiment (cohabitation) and an inoculation challenge were conducted with clams and mussels (Mytilus edulis). Three field exposure experiments were also conducted, in which naive clams were held in sediment (in trays) or out of sediment (in mesh bags) at three high HN prevalence sites on PEI. There was a conversion to HN positive in clams in the proximity experiment and in clams injected with whole blood and cell-free homogenate, but not at statistically significant levels. No mussels or control clams became HN positive. There was a significant conversion to HN positive in as little as 24 and 58 days after transfer with clams held out of sediment and in sediment, respectively. The laboratory and field experiments' results suggest that HN-infected clams are spreading the disease through water from infected clams to naïve individuals and via transplantation from affected to unaffected sites. Some environmental conditions (e.g. abnormally high water temperature and hypoxia-induced sea lettuce [Ulva lacteus] invasion) may make clams susceptible to infections or exacerbate the proliferation of HN.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.166
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.017
GPT teacher head0.239
Teacher spread0.222 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations19
Published2015
Admission routes2
Has abstractyes

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