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The prawns of the genus Macrobrachium (Crustacea, Decapoda, Palaemonidae) with commercial importance: a patentometric view

2017· article· en· W2534679060 on OpenAlexaff
Shehu Latunji Akintola, Cristina Olimpia Chávez-Chong, Ricardo Arencibia Jorge, Olimpia Chong-Carrillo, Marcelo García‐Guerrero, Layla Michán, Héctor Nolasco‐Soria, Fabio Germán Cupul‐Magaña, Fernando Vega‐Villasante

Bibliographic record

VenueLatin American Journal of Aquatic Research · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicCrustacean biology and ecology
Canadian institutionsCanadian Bank Note Company (Canada)
Fundersnot available
KeywordsPalaemonidaeMacrobrachium rosenbergiiDecapodaGenusMacrobrachiumCrustaceanBiologyPrawnFisheryAquacultureReproductionShellfishZoologyEcologyFish <Actinopterygii>Aquatic animal

Abstract

fetched live from OpenAlex

The scientific interest in the genus Macrobrachium was not only from a biological aspect, but also from economic aspect. This paper analyzed the patents identified in several databases using the keyword Macrobrachium. Patents were selected when a species of Macrobrachium was mentioned in main title. The total number of identified patents was 131, of which Chinese authors and institutions have produced more than 90%. Topics addressed refer to culture technologies (41%), nutrition and feeding (26%), reproduction technologies (19%) and pathological diagnosis and treatments (14%). Patents are mainly directed for M. rosenbergii (71%), M. nipponense (28%) and M. superbum (1%). Until now, it has not been attempts to generate patents to American continent species.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.982
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0180.019
Science and technology studies0.0010.000
Scholarly communication0.0020.003
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.048
GPT teacher head0.347
Teacher spread0.299 · 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.

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

Citations13
Published2017
Admission routes1
Has abstractyes

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