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Record W7079542396 · doi:10.26108/7ayr-yn84

American lobster Homarus americanus demographics related to depth and temperature in lobster fishing areas 33 and 34 off Nova Scotia

2023· other· en· W7079542396 on OpenAlexaboutno aff

Bibliographic record

VenueAcadiaU-DEV · 2023
Typeother
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsAmerican lobsterHomarusFishingCarapaceRookeryPopulationDecapodaGeneralized additive model

Abstract

fetched live from OpenAlex

The lobster fishery is the most valuable fishery in Canada, representing over 40% of total seafood landings, with most landings in lobster fishing areas (LFAs) 33 and 34 off Nova Scotia. Canadian lobster landings have been steadily increasing since the 1980s and are projected to continue to increase due to fewer predators and expanding suitable habitat. Within LFAs, lobster are caught up to 90 km from shore. Differences in morphological characteristics between inshore and offshore contingents (if they exist) remain poorly identified and characterized. This study characterized lobster morphometrics, population structure, and other metrics of population status in relation to habitat characteristics of depth and temperature in LFAs 33 and 34 to determine if lobster contingents exist and if so, their relationships to local habitats. Overall, relationships were apparent between lobster morphometrics and environmental factors including depth, bottom temperature, surface temperature, month, soak time, latitude, longitude, and between the lobster morphometrics and lobster condition, sex, carapace hardness, and carapace length. Most environmental variables were collinear, obscuring any significant relationships in all models. Furthermore, deviance explained was low for all GAMs and misclassification rates were high for nearly all multinomial logistic regressions, demonstrating that the models were able to account for little variability in the data. Our results were generally comparable to other studies with a few discrepancies. In conclusion, eliminating the collinearity between variables and recording video footage of lobster at depth would allow us to strengthen our analyses and consider potential differences in lobster behaviour. We did not determine if local contingents exist in the inshore and offshore regions of LFAs 33 and 34 because generalizing habitats to inshore and offshore regions fails to capture habitat characteristics at finer scales of resolution that may affect lobster distributions.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.388
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.010
GPT teacher head0.235
Teacher spread0.225 · 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 designNot applicable
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
Published2023
Admission routes1
Has abstractyes

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