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Record W2011933804 · doi:10.1111/anu.12084

Effect of ration on gonad development of the Pacific geoduck clam,<i>Panopea generosa</i>(Gould, 1850)

2014· article· en· W2011933804 on OpenAlexaff
R Marshall, R. S. McKinley, Christopher M. Pearce

Bibliographic record

VenueAquaculture Nutrition · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Bivalve and Aquaculture Studies
Canadian institutionsVancouver Island UniversityFisheries and Oceans CanadaUniversity of British Columbia
Fundersnot available
KeywordsBiologySpawn (biology)Gonadosomatic IndexAnimal scienceGonadGameteSpermFisheryDevelopment of the gonadsAnatomyBotanyFecundityPopulation

Abstract

fetched live from OpenAlex

The effect of ration on Panopea generosa gonad development was tested over 52 days. Clams were fed Isochrysis sp. and Chaetoceros muelleri (50 : 50 cell count) at rations of 0.8 × 109, 2.4 × 109, 4.0 × 109, 5.6 × 109, 7.2 × 109 and 10.0 × 109 cells clam−1 day−1 (R1, R2, R3, R4, R5 and R6, respectively). The highest ration (R6) caused a 25% die-off within 3 days and was discontinued. Ration did not significantly affect condition index, gonadosomatic index, connective tissue occupation index or oocyte diameter. Clams fed the R5 ration (85% of which spawned from day 26 to 52) were more spent than clams in any other treatment with significantly fewer oocytes mm−2 than those fed the R1, R2 and R3 rations and significantly lower levels of sperm occupation than clams fed any other ration. Spawn percentages were low from day 26 to 52 in R1, R2 and R4 (15, 0 and 0%, respectively). Clams in the R3 treatment had a similar spawn percentage (100% from day 26 to 52) to those in the R5 treatment yet maintained gonads in a more ripened condition with higher levels of gamete occupation, making R3 the most likely ration to maximize gamete output over time.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.005
GPT teacher head0.217
Teacher spread0.212 · 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 source (direct Gemma or distilled Codex), 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

Citations12
Published2014
Admission routes1
Has abstractyes

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