Research Trends in Octopus Biological Studies
Bibliographic record
Abstract
Octopuses represent interesting model studies for different fields of scientific inquiry. The present study provides a bibliometric analysis on research trends in octopuses biological studies. The analysis was executed from January 1985 to December 2020 including scientific products reported in the Web of Science database. The period of study was split into two blocks ("earlier period" (EP): 1985-2010; "recent period" (RP): 2011-2020) to analyze the evolution of the research topics over time. All publications of interest were identified by using the following query: ((AK = octopus) OR (AB = octopus) OR (TI = octopus)). Data information was converted into an R-data frame using bibliometrix. Octopuses studies appeared in 360 different sources in EP, while they increased to 408 in RP. Sixty countries contributed to the octopuses studies in the EP, while they were 78 in the RP. The number of affiliations also increased between EP and RP, with 835 research centers involved in the EP and 1399 in the RP. In the EP 5 clusters (i.e., "growth and nutrition", "pollution impact", "morphology", "neurobiology", "biochemistry") were represented in a thematic map, according to their centrality and density ranking. In the RP the analysis identified 4 clusters (i.e., "growth and nutrition", "ecology", "pollution impact", "genes, behavior, and brain evolution"). The UK with Ireland, and the USA with Canada shared the highest number of publications in the EP, while in the RP, Spain and Portugal were the leading countries. The current data provide significant insight into the evolving trends in octopuses studies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.097 | 0.139 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".