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Bibliographic record
Abstract
The continuous wavelet transform enables the observation of transient/non-stationary cyclicity in time-series. The goal of cyclostratigraphic studies is to define frequency/period in the depth/time domain. By conducting the continuous wavelet transform on cyclostratigraphic data series one can observe and extract cyclic signals/signatures from signals. These results can then be visualized and interpreted enabling one to identify/interpret cyclicity in the geological record, which can be used to construct astrochronological age-models and identify and interpret cyclicity in past and present climate systems. The 'WaverideR' R package builds upon existing literature and existing codebase. The list of articles which are relevant can be grouped in four subjects; cyclostratigraphic data analysis,example data sets,the (continuous) wavelet transform and astronomical solutions. References for the cyclostratigraphic data analysis articles are: Stephen Meyers (2019) <<a href="https://doi.org/10.1016%2Fj.earscirev.2018.11.015" target="_top">doi:10.1016/j.earscirev.2018.11.015</a>>. Mingsong Li, Linda Hinnov, Lee Kump (2019) <<a href="https://doi.org/10.1016%2Fj.cageo.2019.02.011" target="_top">doi:10.1016/j.cageo.2019.02.011</a>> Stephen Meyers (2012)<<a href="https://doi.org/10.1029%2F2012PA002307" target="_top">doi:10.1029/2012PA002307</a>> Mingsong Li, Lee R. Kump, Linda A. Hinnov, Michael E. Mann (2018) <<a href="https://doi.org/10.1016%2Fj.epsl.2018.08.041" target="_top">doi:10.1016/j.epsl.2018.08.041</a>>. Wouters, S., Crucifix, M., Sinnesael, M., Da Silva, A.C., Zeeden, C., Zivanovic, M., Boulvain, F., Devleeschouwer, X. (2022) <<a href="https://doi.org/10.1016%2Fj.earscirev.2021.103894" target="_top">doi:10.1016/j.earscirev.2021.103894</a>>. Wouters, S., Da Silva, A.-C., Boulvain, F., and Devleeschouwer, X. (2021) <<a href="https://doi.org/10.32614%2FRJ-2021-039" target="_top">doi:10.32614/RJ-2021-039</a>>. Huang, Norden E., Zhaohua Wu, Steven R. Long, Kenneth C. Arnold, Xianyao Chen, and Karin Blank (2009) <<a href="https://doi.org/10.1142%2FS1793536909000096" target="_top">doi:10.1142/S1793536909000096</a>>. Cleveland, W. S. (1979)<<a href="https://doi.org/10.1080%2F01621459.1979.10481038" target="_top">doi:10.1080/01621459.1979.10481038</a>> Hurvich, C.M., Simonoff, J.S., and Tsai, C.L. (1998) <<a href="https://doi.org/10.1111%2F1467-9868.00125" target="_top">doi:10.1111/1467-9868.00125</a>>, Golub, G., Heath, M. and Wahba, G. (1979) <<a href="https://doi.org/10.2307%2F1268518" target="_top">doi:10.2307/1268518</a>>. References for the example data articles are: Damien Pas, Linda Hinnov, James E. (Jed) Day, Kenneth Kodama, Matthias Sinnesael, Wei Liu (2018) <<a href="https://doi.org/10.1016%2Fj.epsl.2018.02.010" target="_top">doi:10.1016/j.epsl.2018.02.010</a>>. Steinhilber, Friedhelm, Abreu, Jacksiel, Beer, Juerg , Brunner, Irene, Christl, Marcus, Fischer, Hubertus, HeikkilA, U., Kubik, Peter, Mann, Mathias, Mccracken, K. , Miller, Heinrich, Miyahara, Hiroko, Oerter, Hans , Wilhelms, Frank. (2012 <<a href="https://doi.org/10.1073%2Fpnas.1118965109" target="_top">doi:10.1073/pnas.1118965109</a>>. Christian Zeeden, Frederik Hilgen, Thomas Westerhold, Lucas Lourens, Ursula Röhl, Torsten Bickert (2013) <<a href="https://doi.org/10.1016%2Fj.palaeo.2012.11.009" target="_top">doi:10.1016/j.palaeo.2012.11.009</a>>. References for the (continuous) wavelet transform articles are: Morlet, Jean, Georges Arens, Eliane Fourgeau, and Dominique Glard (1982a) <<a href="https://doi.org/10.1190%2F1.1441328" target="_top">doi:10.1190/1.1441328</a>>. J. Morlet, G. Arens, E. Fourgeau, D. Giard (1982b) <<a href="https://doi.org/10.1190%2F1.1441329" target="_top">doi:10.1190/1.1441329</a>>. Torrence, C., and G. P. Compo (1998)<<a href="https://paos.colorado.edu/research/wavelets/bams_79_01_0061.pdf" target="_top">https://paos.colorado.edu/research/wavelets/bams_79_01_0061.pdf</a>>, Gouhier TC, Grinsted A, Simko V (2021) <<a href="https://github.com/tgouhier/biwavelet" target="_top">https://github.com/tgouhier/biwavelet</a>>. Angi Roesch and Harald Schmidbauer (2018) <<a href="https://CRAN.R-project.org/package=WaveletComp" target="_top">https://CRAN.R-project.org/package=WaveletComp</a>>. Russell, Brian, and Jiajun Han (2016)<<a href="https://www.crewes.org/Documents/ResearchReports/2016/CRR201668.pdf" target="_top">https://www.crewes.org/Documents/ResearchReports/2016/CRR201668.pdf</a>>. Gabor, Dennis (1946) <<a href="http://genesis.eecg.toronto.edu/gabor1946.pdf" target="_top">http://genesis.eecg.toronto.edu/gabor1946.pdf</a>>. J. Laskar, P. Robutel, F. Joutel, M. Gastineau, A.C.M. Correia, and B. Levrard, B. (2004) <<a href="https://doi.org/10.1051%2F0004-6361%3A20041335" target="_top">doi:10.1051/0004-6361:20041335</a>>. Laskar, J., Fienga, A., Gastineau, M., Manche, H. (2011a) <<a href="https://doi.org/10.1051%2F0004-6361%2F201116836" target="_top">doi:10.1051/0004-6361/201116836</a>>. References for the astronomical solutions articles are: Laskar, J., Gastineau, M., Delisle, J.-B., Farres, A., Fienga, A. (2011b <<a href="https://doi.org/10.1051%2F0004-6361%2F201117504" target="_top">doi:10.1051/0004-6361/201117504</a>>. J. Laskar (2019) <<a href="https://doi.org/10.1016%2FB978-0-12-824360-2.00004-8" target="_top">doi:10.1016/B978-0-12-824360-2.00004-8</a>>. Zeebe, Richard E (2017) <<a href="https://doi.org/10.3847%2F1538-3881%2Faa8cce" target="_top">doi:10.3847/1538-3881/aa8cce</a>>. Zeebe, R. E. and Lourens, L. J. (2019) <<a href="https://doi.org/10.1016%2Fj.epsl.2022.117595" target="_top">doi:10.1016/j.epsl.2022.117595</a>>. Richard E. Zeebe Lucas J. Lourens (2022) <<a href="https://doi.org/10.1126%2Fscience.aax0612" target="_top">doi:10.1126/science.aax0612</a>>.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.008 |
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