18 research outputs found
Trialling meta-research in comparative cognition: claims and statistical inference in animal physical cognition
Scientific disciplines face concerns about replicability and statistical inference, and these concerns are also relevant in animal cognition research. This paper presents a first attempt to assess how researchers make and publish claims about animal physical cognition, and the statistical inferences they use to support them. We surveyed 116 published experiments from 63 papers on physical cognition, covering 43 different species. The most common tasks in our sample were trap-tube tasks (14 papers), other tool use tasks (13 papers), means-end understanding and string-pulling tasks (11 papers), object choice and object permanence tasks (9 papers) and access tasks (5 papers). This sample is not representative of the full scope of physical cognition research; however, it does provide data on the types of statistical design and publication decisions researchers have adopted. Across the 116 experiments, the median sample size was 7. Depending on the definitions we used, we estimated that between 44% and 59% of our sample of papers made positive claims about animals’ physical cognitive abilities, between 24% and 46% made inconclusive claims, and between 10% and 17% made negative claims. Several failures of animals to pass physical cognition tasks were reported. Although our measures had low inter-observer reliability, these findings show that negative results can and have been published in the field. However, publication bias is still present, and consistent with this, we observed a drop in the frequency of p-values above .05. This suggests that some non-significant results have not been published. More promisingly, we found that researchers are likely making many correct statistical inferences at the individual-level. The strength of evidence of statistical effects at the group-level was weaker, and its p-value distribution was consistent with some effect sizes being overestimated. Studies such as ours can form part of a wider investigation into statistical reliability in comparative cognition. However, future work should focus on developing the validity and reliability of the measurements they use, and we offer some starting points
Trialling Meta-Research in Comparative Cognition: Claims and Statistical Inference in Animal Physical Cognition.
Scientific disciplines face concerns about replicability and statistical inference, and these concerns are also relevant in animal cognition research. This paper presents a first attempt to assess how researchers make and publish claims about animal physical cognition, and the statistical inferences they use to support them. We surveyed 116 published experiments from 63 papers on physical cognition, covering 43 different species. The most common tasks in our sample were trap-tube tasks (14 papers), other tool use tasks (13 papers), means-end understanding and string-pulling tasks (11 papers), object choice and object permanence tasks (9 papers) and access tasks (5 papers). This sample is not representative of the full scope of physical cognition research; however, it does provide data on the types of statistical design and publication decisions researchers have adopted. Across the 116 experiments, the median sample size was 7. Depending on the definitions we used, we estimated that between 44% and 59% of our sample of papers made positive claims about animals' physical cognitive abilities, between 24% and 46% made inconclusive claims, and between 10% and 17% made negative claims. Several failures of animals to pass physical cognition tasks were reported. Although our measures had low inter-observer reliability, these findings show that negative results can and have been published in the field. However, publication bias is still present, and consistent with this, we observed a drop in the frequency of p-values above .05. This suggests that some non-significant results have not been published. More promisingly, we found that researchers are likely making many correct statistical inferences at the individual-level. The strength of evidence of statistical effects at the group-level was weaker, and its p-value distribution was consistent with some effect sizes being overestimated. Studies such as ours can form part of a wider investigation into statistical reliability in comparative cognition. However, future work should focus on developing the validity and reliability of the measurements they use, and we offer some starting points.BB/M011194/
Individual performance across motoric self-regulation tasks are not correlated for pet dogs
Fate and Uptake of Pharmaceuticals in Soil–Earthworm Systems
Pharmaceuticals present a potential threat to soil organisms, yet our understanding of their fate and uptake in soil systems is limited. This study therefore investigated the fate and uptake of 14C-labeled carbamazepine, diclofenac, fluoxetine, and orlistat in soil–earthworm systems. Sorption coefficients increased in the order of carbamazepine < diclofenac < fluoxetine < orlistat. Dissipation of 14C varied by compound, and for orlistat, there was evidence of formation of nonextractable residues. Uptake of 14C was seen for all compounds. Depuration studies showed complete elimination of 14C for carbamazepine and fluoxetine treatments and partial elimination for orlistat and diclofenac, with greater than 30% of the 14C remaining in the tissue at the end of the experiment. Pore-water-based bioconcentration factors (BCFs), based on uptake and elimination of 14C, increased in the order carbamazepine < diclofenac < fluoxetine and orlistat. Liquid chromatography–tandem mass spectrometry and liquid chromatography–Fourier transform mass spectrometry indicated that the observed uptake in the fluoxetine and carbamazepine treatments was due to the parent compounds but that diclofenac was degraded in the test system so uptake was due to unidentifiable transformation products. Comparison of our data with outputs of quantitative structure−activity relationships for estimating BCFs in worms showed that these models tend to overestimate pharmaceutical BCFs so new models are needed