MétaCan
Menu
Back to cohort

SEASONAL VARIATION IN MACRO-MICRONUTRIENT COMPOSITIONS OF THE FLESH AND SHELL OF THE PORTUNID CRAB Callinectes amnicola (De Rochebrune, 1883) FROM THE COASTAL WATERS OF SOUTHWEST NIGERIA

2019· article· en· W4407118042 on OpenAlexaff
Rasheed Olatunji Moruf, Abdulwakil Olawale Saba, Joy Chukwu-Osazuwa, Isa Olalekan Elegbede

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFish Biology and Ecology Studies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsCallinectesFleshFisheryMicronutrientMacroBiologyGeographyCrustaceanMedicine

Abstract

fetched live from OpenAlex

Portunids are decapod crustaceans of high economic importance. Seasonal variation in macronutrient and micronutrients contents of Callinectes amnicola from three interconnecting lagoons were investigated using standard methods. The percentages of protein and moisture contents in the flesh were higher than that of the shell, while higher ash and nitrogen free extract were obtained in the shell. Crude fibres was not detected in flesh of C. amnicola but detected in shells with values ranging from 0.30 ±0.72 % (C. amnicola from Lagos Lagoon) to 0.55 ±2.15 % (C. amnicola from Badagry Lagoon). There were statistical differences (P ˂ 0.05) in crude fibre and carbohydrate levels of the crab shell during wet and dry seasons while significant difference exist in protein level only in wet season. Protein showed negative correlations with all the minerals in crabs from Badagry and Epe Lagoons but positive correlation with all examined minerals in Lagos Lagoon crabs. The study demonstrated that Callinectes amnicola is rich in macro-micronutrients and characterized by low lipid content (< 3%). The nutrient biochemical constituents in the crab species vary with season

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.373
Threshold uncertainty score0.828

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 science0.0010.001
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 head0.075
GPT teacher head0.390
Teacher spread0.314 · 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

Citations8
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueDOAJ (DOAJ: Directory of Open Access Journals)Same topicFish Biology and Ecology StudiesFrench-language works237,207