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1,509 results for “Calibrations”
FIGURE 13 in Phylogenetically vetted and stratigraphically constrained fossil calibrations within Aves
FIGURE 13. Phylogenetic tree showing position of Messelirrisor halcyrostris, illustrating the divergence calibrated by SMF-ME 1883a+b.
FIGURE 3 in Phylogenetically vetted and stratigraphically constrained fossil calibrations within Aves
FIGURE 3. Phylogenetic tree showing position of Waimanu manneringi, illustrating the divergence calibrated by CM zfa35.
FIGURE 12 in Phylogenetically vetted and stratigraphically constrained fossil calibrations within Aves
FIGURE 12. Stratigraphic distribution of fossil Pan-Psittaciformes in the Paleogene. The minimum possible age of the calibrating specimen NMH A6207 is presented, and midpoints of age ranges are shown for the ages of other Paleogene parrot specimens. Note that the London Clay Formation also contains multiple associated skeletons and isolated bones in addition to the holotype of Pulchrapollia gracilis that serves as a calibration point.
FIGURE 9 in Phylogenetically vetted and stratigraphically constrained fossil calibrations within Aves
FIGURE 9. Phylogenetic tree showing position of Sandcoleus copiosus, illustrating the divergence calibrated by USNM 433912.
FIGURE 5 in Phylogenetically vetted and stratigraphically constrained fossil calibrations within Aves
FIGURE 5. Phylogenetic tree showing position of Primobucco mcgrewi, illustrating the divergence calibrated by USNM 336484.
FIGURE 10. Calibration diagram for mammals, excluding Archonta. Euarchontoglires continued into Figure 11 in Constraints on the timescale of animal evolutionary history
FIGURE 10. Calibration diagram for mammals, excluding Archonta. Euarchontoglires continued into Figure 11.
Fig. 3 in Time-calibrated molecular phylogeny reveals a Miocene-Pliocene diversification in the Amazon miniature killifish genus Fluviphylax (Cyprinodontiformes: Cyprinodontoidei)
Fig. 3 Time-calibrated phylogeny of the Cyprinodontoidei and Fluviphylax obtained from the Bayesian dating analysis in Beast v.1.8. Bars represent maximum and minimum date estimates for each node, and the numbers are node divergence mean ages. Arrows indicate the nodes
Fig. 1 in Time-calibrated molecular phylogeny reveals a Miocene-Pliocene diversification in the Amazon miniature killifish genus Fluviphylax (Cyprinodontiformes: Cyprinodontoidei)
Fig. 1 Distribution map of Fluviphylax: F. obscurus (white dot), F. palikur (orange dot), F. pygmaeus (yellow dot), F. simplex (blue dot), F. zonatus (red dot), Fluviphylax sp. A (green dot), Fluviphylax sp. B (brown dot), and Fluviphylax sp. C (purple dot)
Fig. 2 Phylogenetic relationships among 30 in Time-calibrated molecular phylogeny reveals a Miocene-Pliocene diversification in the Amazon miniature killifish genus Fluviphylax (Cyprinodontiformes: Cyprinodontoidei)
Fig. 2 Phylogenetic relationships among 30 species of Cyprinodontoidei, including all nominal species of Fluviphylax and three undescribed species, inferred by using partial sequences of the nuclear-encoded genes GLYT1, ENC1, RAG1, MYH6, and SREB2 and the mitochondrial gene COI, total of 5880 bp. Numbers left to the bar indicate posterior
FIGURE 1 in Fossil calibration dates for molecular phylogenetic analysis of snakes 2: Caenophidia, Colubroidea, Elapoidea, Colubridae
FIGURE 1. Phylogeny of Caenophidia from Pyron et al. (2013a) temporally calibrated on minimum ages reported here. Taxon names in grey have not been described in the fossil record. Taxon names in black have been described from fossils. See Holman (2000) and Szyndlar (2012) for records. Taxa labeled with two identifiers represent the most inclusive clades subtended by those identifiers following Pyron et al. (2013a).
FIGURE 3. A in How to date a dragonfly: Fossil calibrations for odonates
FIGURE 3. A cladogram of Odonata (adapted from Carle et al., 2015) showing the phylogenetic relationships among Anisopteran families. The species highlighted in blue are the crown group fossils discussed in this manuscript. Node numbers are listed in the order in which they are discussed in the manuscript. Node ages indicate the minimum age of the crown fossil used. The question mark indicates weak support for the node Petaluridae + Gomphidae (see Carle et al., 2015 for more details). Extinct species are indicated by a dagger. Note: nodes 2, 5, 6, 8, 9, and 10 are drawn for simplicity, but these fossil taxa may be nested deep within the family to which they are assigned. The fossils shown in the tree are not sister to the rest of the members of the family.
FIGURE 1 in How to date a dragonfly: Fossil calibrations for odonates
FIGURE 1. Wing venation of Anisoptera (after Bechly et al., 2001) (details for the abbreviations in Appendix 1).
FIGURE 2 in How to date a dragonfly: Fossil calibrations for odonates
FIGURE 2. Wing venation of Liassophlebia sp., specimen TUClP In 192, from the Liassic alpha of Pechgraben in Germany (Bechly, 1999) (Scale equals 10 mm)
VLBI Calibrator Grid at 600Mhz for CHIME/FRB Outriggers
<p>All positions from the <a href="https://astrogeo.org/sol/rfc/rfc_2024b/" target="_blank" rel="noopener">RFC</a>. Survey description in <a href="https://arxiv.org/abs/2409.11476" target="_blank" rel="noopener">Andrew et al 2024 </a>.</p>
Data of active calibration near the surface
<p>Active calibration data acquired at varying distances to the surface</p>
Data from: Time-calibrated molecular phylogeny of pteropods
Pteropods are a widespread group of holoplanktonic gastropod molluscs and are uniquely suitable for study of long-term evolutionary processes in the open ocean because they are the only living metazoan plankton with a good fossil record. Pteropods have been proposed as bioindicators to monitor the impacts of ocean acidification and in consequence have attracted considerable research interest, however, a robust evolutionary framework for the group is still lacking. Here we reconstruct their phylogenetic relationships and examine the evolutionary history of pteropods based on combined analyses of Cytochrome Oxidase I, 28S, and 18S ribosomal rRNA sequences and a molecular clock calibrated using fossils and the estimated timing of the formation of the Isthmus of Panama. Euthecosomes with uncoiled shells were monophyletic with Creseis as the earliest diverging lineage, estimated at 41–38 million years ago (mya). The coiled euthecosomes (Limacina, Heliconoides, Thielea) were not monophyletic contrary to the accepted morphology-based taxonomy; however, due to their high rate heterogeneity no firm conclusions can be drawn. We found strong support for monophyly of most euthecosome genera, but Clio appeared as a polyphyletic group, and Diacavolinia grouped within Cavolinia, making the latter genus paraphyletic. The highest evolutionary rates were observed in Heliconoides inflatus and Limacina bulimoides for both 28S and 18S partitions. Using a fossil-calibrated phylogeny that sets the first occurrence of coiled euthecosomes at 79–66 mya, we estimate that uncoiled euthecosomes evolved 51–42 mya and that most extant uncoiled genera originated 40–15 mya. These findings are congruent with a molecular clock analysis using the Isthmus of Panama formation as an independent calibration. Although not all phylogenetic relationships could be resolved based on three molecular markers, this study provides a useful resource to study pteropod diversity and provides general insight into the processes that generate and maintain their diversity in the open ocean.
Figure 23. Temporally calibrated cladogram representing a in The skull of the titanosaur Tapuiasaurus macedoi (Dinosauria: Sauropoda), a basal titanosaur from the Lower Cretaceous of Brazil
Figure 23. Temporally calibrated cladogram representing a reduced consensus of 34 MPTs generated in a cladistic analysis of 31 taxa and 246 characters (see text for details). The reduced consensus was generated using the iterPCR script in TNT (see Pol & Escapa, 2009), which identified Tapuiasaurus and Nemegtosaurus as wildcard taxa that linked with 13 different lithostrotian taxa in the MPTs (labelled a–c and d–m, respectively). The italicized numbers at nodes within Titanosauria represent decay indices>1. The coloured bars represent the temporal distribution of diplodocoid (brown) and macronarian (purple) taxa; in all cases their vertical extent reflects stratigraphic uncertainty rather than a true range. Dates at epoch and stage boundaries are based on Cohen et al. (2013). Coloration of chronostratigraphic units follows the Commission for the Geological Map of the World (http://www.ccgm.org).
Calibration data for reflection bridge using SR 844 lock-in amplifier
<p>Calibration data for reflection brigde using SR 844 lock-in amplifier</p>
Design, construction and traceable calibration of a phosphor-based fibre-optic thermometer from 0 °C to 650 °C
<p>Dataset associated with publication DOI <a href="https://doi.org/10.1088/1361-6501/abee53">https://doi.org/10.1088/1361-6501/abee53</a></p>
fair calibration data
<p><strong>Note: please be careful selecting calibrations in your own work; the newest isn't always the "best", or the right one for your needs.</strong></p> <p><strong>If you're unsure, please contact me.</strong></p> <p>If you use fair calibrations in your own work, please cite:</p> <p>Smith, C., Cummins, D. P., Fredriksen, H.-B., Nicholls, Z., Meinshausen, M., Allen, M., Jenkins, S., Leach, N., Mathison, C., and Partanen, A.-I.: fair-calibrate v1.4.1: calibration, constraining, and validation of the FaIR simple climate model for reliable future climate projections, Geosci. Model Dev., 17, 8569–8592, https://doi.org/10.5194/gmd-17-8569-2024, 2024.</p> <p> </p> <p>This dataset contains the full data, input scripts and produced output data for the <strong>updated-2023 calibration</strong><strong> </strong>of <strong>fair v2.2.2</strong>.</p> <p>The zipfile contains everything, allowing you perform your own analysis. The <a href="https://github.com/chrisroadmap/fair-calibrate/tree/v1.4.3">GitHub version</a> contains enough for "bare bones" reproducibility. In addition, I have tried to provide all of the individual files that would be needed to run a historical run of fair.</p> <p><strong>fair v2.2.2</strong></p> <p>Obtainable from https://pypi.org/project/fair/</p> <p>From the command line:</p> <p><code>pip install fair==2.2.2</code></p> <p>or</p> <p><code>conda install -c conda-forge fair==2.2.2</code></p> <p><strong>Calibration v1.5</strong></p> <p>A 1.6 million member prior and 841 member posterior are implemented.</p> <ul> <li>1.6 million prior ensemble</li> <li>Climate response calibrated on 49 abrupt-4xCO2 experiments from CMIP6 and sampled using correlated kernel density estimates</li> <li>Methane lifetime calibrated on 4 AerChemMIP experiments for 1850 and 2014 (Thornhill et al. 2021a, 2021b). Unlike other variables which are sampled around some prior uncertainty, only the best estimate historical calibration is used. The base (1750) lifetime has been fixed and consistently used across projections</li> <li>Carbon cycle uses the parameters from Leach et al. 2021 calibrated for FaIR 2.0.0 using 11 C4MIP models.</li> <li>Aerosol cloud interactions depend on SO2, BC and OC, using new calibrations from 13 RFMIP and AerChemMIP models, with the APRP code fixed by Mark Zelinka (Zelinka et al. 2023). Prior is a trapezoidal distribution with vertices at (-2.2, -1.6, -0.4, +0.2) W/m2.</li> <li>Aerosol radiation interactions use prior values from AR6 Ch6, with best estimates and uncertainties scaled to create a prior in the range of -0.6 to 0.0 W/m2.</li> <li>Ozone uses the same methodology as AR6 (Smith et al. 2021).</li> <li>Effective radiative forcing uncertainty follows the distributions in AR6, with asymmetric distributions switched to skew-normal.</li> <li>Contrails are excluded from the calibration</li> <li>fair version bumped to v2.2.2</li> <li>many more individual files included in the calibration output which should make plugging and playing easier</li> </ul> <p><strong>Constraint sets</strong></p> <p>AR6_updated_no-contrails (v1.5.1)</p> <p>As v1.5.0, except</p> <ul> <li>Emissions and concentrations from CMIP6 historical</li> <li>Volcanic forcing time series from CMIP6.</li> <li>Solar forcing time series from CMIP6.</li> <li>Warming 1995-2014 relative to 1850-1900 range from AR6.</li> <li>CO2 concentrations constrained to AR6 estimate for 2014.</li> <li>Ocean heat content from IGCC (1971-2018), linear, from AR6.</li> <li>Aerosol ERF, ERFari and ERFaci as in the fair calibration from AR6 WG1 Chapter 7 (e.g. -1.68, -1.15, -0.60)</li> </ul> <p><strong>updated_2023 (v1.5.0)</strong></p> <ul> <li>841-member posterior (deliberately chosen).</li> <li>Emissions and concentrations from CMIP7 historical (Zeb Nicholls, Jarmo Kikstra et al.)</li> <li>Volcanic forcing time series updated to use CMIP7 (from Thomas Aubry and collaborators).</li> <li>Solar forcing time series updated to use CMIP7 (Funke et al. 2024).</li> <li>Temperature from IGCC 2024 (Forster et al. 2025) (1850-2024, mean of 4 datasets).</li> <li>Warming 2004-2023 relative to 1850-1900 range from IGCC 2023 (Forster et al. 2024).</li> <li>CO2 concentrations constrained to IGCC estimate for 2023.</li> <li>Ocean heat content from IGCC (1971-2020), linear, from IGCC.</li> <li>two step constraining procedure used: first RMSE of less than 0.19K, then 8-variable distribution fitting.</li> <li>Aerosol ERF, ERFari and ERFaci as in AR6 WG1</li> <li>No future warming constraints</li> </ul> <p><strong>Performance relative to AR6 assessed ranges</strong></p> <p>On request, as Zenodo seems to have removed the ability to format tables in the dataset description.</p> <p><strong>References</strong></p> <ul> <li>Forster et al. 2024: <a href="https://doi.org/10.5194/essd-16-2625-2024" rel="nofollow">https://doi.org/10.5194/essd-16-2625-2024</a></li> <li>Forster et al. 2025: <a href="https://doi.org/10.5194/essd-17-2641-2025" rel="nofollow">https://doi.org/10.5194/essd-17-2641-2025</a></li> <li>Funke et al. 2024: <a href="https://doi.org/10.5194/gmd-17-1217-2024" rel="nofollow">https://doi.org/10.5194/gmd-17-1217-2024</a></li> <li>Leach et al. 2021: <a href="https://doi.org/10.5194/gmd-14-3007-2021" rel="nofollow">https://doi.org/10.5194/gmd-14-3007-2021</a></li> <li>Smith et al. 2021: <a href="https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6_WGI_FGD_Chapter07_SM.pdf" rel="nofollow">https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6_WGI_FGD_Chapter07_SM.pdf</a></li> <li>Thornhill et al. 2021a: <a href="https://doi.org/10.5194/acp-21-853-2021" rel="nofollow">https://doi.org/10.5194/acp-21-853-2021</a></li> <li>Thornhill et al. 2021b: <a href="https://doi.org/10.5194/acp-21-1105-2021" rel="nofollow">https://doi.org/10.5194/acp-21-1105-2021</a></li> <li>Zelinka et al. 2023: <a href="https://doi.org/10.5194/acp-23-8879-2023" rel="nofollow">https://doi.org/10.5194/acp-23-8879-2023</a></li> </ul>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.