Predatory behaviour and prey-capture decision-making by the web-weaving spider <i>Micrathena</i> <i>sagittata</i>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Optimal-foraging theory predicts how a predator would feed most efficiently when faced with a choice of two types of prey differing in profitability and density in the habitat. The predator should focus only on the more profitable prey, since any prey item eaten by the predator has a cost in terms of the time and resources taken to subdue and eat it. A study of the hunting behaviour and prey-type selection of the web-weaving spider Micrathena sagittata (Walckenaer, 1841) (Araneae: Araneidae) in the field is documented. In the first part of the study, prey of two sizes were offered in four sectors of the web (top, bottom, right, and left). A prey item was provided at one position of the web at a time. Attack time was recorded at each position. Also, choice and no-choice tests were carried out by offering prey in opposing web sectors (top and bottom) simultaneously. Large prey were more successfully captured in the upper parts than in the bottom parts of the web. In the choice test, spiders always preferred large prey to small prey, while in the no-choice test, spiders always responded to the first stimulus received. Two different attack strategies, depending on prey size, were observed. Hunting strategies and prey-size preference can be related to the cost of web construction and profitability of the prey type.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it