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Record W3089120364 · doi:10.15407/fmmit2020.30.071

Orthogonal transformations and moments in digital information processing

2020· article· en· W3089120364 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuePhysico-mathematical modelling and informational technologies · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAdvanced Scientific Research Methods
Canadian institutionsnot available
Fundersnot available
KeywordsMathematicsCombinatoricsPhysicsStatistics

Abstract

fetched live from OpenAlex

The method of application of the theory of spectral schedules, theory of moments and statistical-probabilistic methods of processing of the digital information received at preparation of sportsmen for competitive activity, in particular at data processing of heart rate (heart rate) is offered in the work. The paper shows the relationship of the moments of the distribution function with the generalized spectra of orthogonal decompositions, considers the question of determining the sample size to obtain research results. References Pianylo, Ya. D. (2011). Proektsiino-iteratsiini metody rozviazuvannia priamykh ta obernenykh zadach perenosu. Lviv: Splain. Bat, M. (1980). Spektralnyi analiz v geofizike. Moskva. Nedra. Gold, B., Reider, CH. (1973). TSifrovaia obrabotka signalov. Moskva. Sov. radio. Suetin, P. K. (2005). Klassicheskie ortogonalnye mnogochleny 3-e izd. pererab. i dop. M. FIZMATLIT. Dzhekson, D. (1948). Riady fure i ortogonalnye polinomy. Perevod s angliiskogo. Gosudarstvennoe izdatelstvo inostrannoi literatury. Matsko, I. Y., Yavorskyi, I. M., Yuzefovych, R. M., Semenov, P. O. (2018). Statystychnyi vektorno-tenzornyi analiz vibratsii tsentryfuhy z rozvynutym defektom obertovoho vuzla. Fizyko-khimichna mekhanika materialiv, 2, 140-147. Morozova, H. V., Sukharkova, O. I. (2012). Identyfikatsiia fihur na ploshchyni za dopomohoiu tsentralnykh momentiv yikh zobrazhen. Prykladna heometriia ta inzhenerna hrafika, 90, 200-205. Avramenko, V. I., Karimov, I. K. (2013). Teoriia ymovirnostei i matematychna statystyka : navch. posibnyk 2-he vyd., pererob. i dop.Dniprodzerzhynsk : DDTU. Gilmore, J. F., Pemberton, W. B. (1984). A suivery of aircraft classification algorithms. 7th Int. Conf. On PR., Montreal, 559-562. Wolf, S., Louvion, J. R. (1979). Considerations sur les formes: pseudo symetrie representation. 2e congres AFCET-IRIA/ Reconnassance des Formes et Intelligence Artificielle, Toulouse. 381-387. Dudani, J. A., Breeding, K. J. (1997). Aircraft identification by moments invariants. IEEE Trans. On Computers. Hilmor, Dzh. F., Pemberton, W. B. Nabir alhorytmiv klasyfikatsii litakiv. 7th Int. Konf. Pro PR., Monreal, 559-562. Volf, S., Luvion, Dzh. R. (1979). Rozghliad sur les formes: psevdosymetrychne predstavlennia. 2e konhresy AFCET-IRIA / Reconnassance des Formes et Intelligence Artificielle, Tuluza. 381-387. Dudani, Zh. A. (1997). Identyfikatsiia litaka za momentamy invariantiv. IEEE Trans. Pro kompiutery.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.920
Threshold uncertainty score0.284

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.004
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.061
GPT teacher head0.282
Teacher spread0.221 · 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