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Record W2944075585

Usage of the iterative photo-computing method in specifying of bird egg radiuses curvature

2018· article· en· W2944075585 on OpenAlexaboutno aff
Ivan S. Mytiai, А. V. Matsyura

Bibliographic record

VenueUkrainian Journal of Ecology · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLeaf Properties and Growth Measurement
Canadian institutionsnot available
Fundersnot available
KeywordsCurvatureBird eggBiologyEcologyZoologyMathematicsGeometry
DOInot available

Abstract

fetched live from OpenAlex

The egg shape, as a description datum about adult bird is an important object for research work closely allied with the bird adaptation to brood under different environmental conditions. Besides, it is possible to use this approach as an additional research instrument for general bird evolution study, ecological proximity, taxonomy, etc. Moreover, at the same time egg shape profile is the mostly suitable characteristic for intravital study above-mentioned aspects. Keywords: Egg shape; photo-computing method; egg radius; curvature References: Anderson, M. (1978). Optimal egg shape in waders. Ornis Fennica, 55, 105-109. Âvila, D. D. (2014). Aplicacion de las funciones elipticas de Fourier para la description de la forma de los liuevos de las aves. Rev. Biol. Trop, 62(4), 1469-1480. Baker, D. E. (2002). A geometric method for determining shape of bird eggs. The Auk, 119, 1179-1186. https://doi.org/10.1642/0004-8038(2002)119(1179:AGMFDS)2.0.CO;2. Ban, M., Barta, Z., Munoz, A. R., Takasu, F., Nakamura, H., & Moskat, C. (2011). The analysis of common cuckoo’s egg shape in relation to its hosts’ in two geographically distant areas. Journal of Zoology, 284(2), 77-150. Biggins, J. D., Thompson, J. E., & Birkhead, T. R. (2018). Accurately quantifying the shape of birds’ eggs. Ecology and Evolution, 1-11. https://doi.org/10.1002/ece3.4412 Barta, Z., & Szekely, T. (1997). The optimal shape of avian eggs. Functional Ecol, 11, P. 656-662. Bridge, E. S., Boughton, R. K., Aldredge, R. A., Harrison, T. E., Bowman, R., & Schoech, S. J. (2007). Measuring egg size using digital photography: testing Hoyt`s method using Florida Scrub-Jay eggs. Journal of Field Ornithology, 78,109-116. DOI: 10.1111/j.1557-9263.2006.00092.x Cundy, H., & Rollett A. (1989). Mathematical Models. Third Edition. Stradbroke, Tarquin Pub. Dixon, R. (1991). Mathographics. New York, Dover. Deeming, D. C., & Ruta, M. (2014). Egg shape changes at the theropod-bird transition, and a morphometric study of amniote eggs. R. Soc. Open Sci, 1. doi:10.1098/rsos.140311 Deeming, D. C. (2018). Effect of composition on shape of bird eggs. Journal of Avian Biology, 49(1), 1-7. doi: 10.1111/jav.01528. Frantsevich, L. (2010). Planimetry of the egg shape parameters. Available from: http://www.biometrica.tomsk.ru/planirus.htm/ Accessed on 10.11.2018. (In Russian) Fuhrer-Nagy, G. (2002). Mathematical modeling of bird egg curves. Aquila, 107/108, 67-73. Heck, A. (2010). Mathematical Brooding over an Egg. Convergence, DOI:10.4169/loci002842. Johnson, L. S., Leyhe, J. E., & Werner, C. (2001). The shape of eggs in different-size clutches of the/ House Wren (Troglodytes aedon). Can. J. Zool, 79, 1527-1531. Iwamoto, T. (2011). Many Shapes of Bird's Eggs. Available from: http://www.takayaiwamoto.com/Egg_Draw/Other_Birds_Egg.html/ Accessed on 25.10.2018 Hutchinson, J. M. C. (2000). Three into two doesn’t go: two-dimensional models of bird eggs, snail shells and plant roots // Biological Journal of the Linnean Society, 70, 161-187. doi:10.1006/bijl.1999.0395 Gemperle, M. E., Preston, F. W. (1955). Variation of shape in the eggs of the common tern in the clutch-sequence. Auk, 72, 184-198. Koller, J. (2000). Mathematische Basteleien. Availble from: http://www.mathematische-basteleien.de/index.htm/ Accessed on 04.10.2018 Kostin, Y. V. (1977). About methodology of oomorphological researches and unification of descriptions of oological material. In Metodiki issledovaniya produktivnosti i struktury vidov ptits v predelakh ikh arealov. (Methods of the study of the productivity and structure of bird species within their areals.) Vilnius (In Russian) Mao, K. M., Murakami, A., Iwasawa, A., & Yoshizaki, N. (2007). The asymmetry of avian egg-shape: an adaptation for reproduction on dry land. J Anat, 210(6), 741-748. doi:10.1111/j.1469-7580.2007.00737.x Mattas, �?. (2001). Uraovani tvar u ptaaich vajec. Sylvia, 37, 17-25. Mieszkalski, L. (2014). Method of mathematical modelling Of the surface of the egg shell shape, egg yolk and air chamber of chicken eggs. Agricultural Engineering, 3(151), 93-104. Mytiai, I. S. (2003). New method for the complex estimation of a form of the egg. Branta, 6, 179-192. (In Russian) Mytia�?, �?. S. (2008). Using modern technologies in researching of bird eggs. Zaporozhye National University Journal. Series Biology, 175-183. (In Russian) Mytiai, I. S., & Matsyura, A. V. (2017). Geometrical standards in shapes of avian eggs. Ukrainian Journal of Ecology, 7(3), 264-282. doi: 10.15421/2017_78 Moller, H. (2009). Das 2:3-Ei-ein praktikables Eimodell. Available from: http://www.math.uni-muenster.de/u/mollerh/data/ZweiDreiEi.pdf/ Accessed on 05.11.2018 Myand, R. (1988). Intrapopulational variability of bird eggs. Tallin, Valgu (In Russian) Murray, C. M., Piller, K. R., & Merchant, M. (2013). Salinity and Egg Shape Variation: A Geometric Morphometric Analysis // Journal of Herpetology, 47(1), 15-23. Narushin, V. G. (2001). Shape geometry of the avian egg. J. Agric. Engin. Res, 79, 441-448. Nedomova, S., & Buchar, J. (2014). Goose eggshell geometry. Res. Agr. Eng, 60, 100-106. Nishiyama, Y. (2010). The Mathematics of Egg Shape. Available from: http://www.osaka-ue.ac.jp/zemi/nishiyama/math2010/egg.pdf Accessed on 15.11.2018 Paganelli, C. V., Olszowka, A., & Ar, A. (1974). The avian egg: surface area, volume, and density. The Condor, 76, 319-325. Petrovi�?, �?., & Obradovi�?, �?. (2010). The complement of the hugelschaffer’s сonstruction of the egg curve. Avalable from: https://www.researchgate.net/publication/273139632/ Accessed on 20.11.2018. Preston, F. W. (1953). The shapes of birds egg. The Auk, 70, 160-182. Preston, F. W. (1957a). Two New Devices for Measuring the Shapes of Birds' Eggs. The Auk, 74, 386-388. Preston, F. W. (1968). The shapes of birds eggs: mathematical aspects. The Auk, 85, 454-463. Reid, W. S., Buckley, D. J., Hunt, J. R., & Prices, K. (1974). A digital instrument for egg shape index measurement. Canadian Journal of Animal Science, 55, 87-92. Stoddard, M. C., Yong, E. H., Akkaynak, D., Sheard, C., Tobias, J. A., & Mahadevan, L. (2017). Avian egg shape: form, function, and evolution. Science, 356, 1249-1254. Todd, P. H., & Smart, I. H. M. (1984). The shape of birds’ eggs. J. Theor. Biol, 106, 239-243. Troscianko, J. (2014). A simple tool for calculating egg shape, volume and surface area from digital images. Ibis, 156(4), 874-878. Yamamoto, N. (2016). We Find an Equation of Egg Shaped Curve. Available from: http://www.geocities.jp/nyjp07/index_egg_E.html/ Accessed on 02.11.2018

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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.

Opus teacher head0.047
GPT teacher head0.273
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations3
Published2018
Admission routes1
Has abstractyes

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