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Record W3010118735 · doi:10.1016/j.jpeds.2020.01.069

Neonatal Intensive Care Unit-Level Patent Ductus Arteriosus Treatment Rates and Outcomes in Infants Born Extremely Preterm

2020· article· en· W3010118735 on OpenAlexafffund
Tetsuya Isayama, Satoshi Kusuda, Brian Reichman, Shoo K. Lee, Liisa Lehtonen, Mikael Norman, Mark Adams, Dirk Bassler, Kjell Helenius, Stellan Håkansson, Junmin Yang, Amish Jain, Prakesh S. Shah, Adele Harrison, Anne Synnes, Joseph Ting, Zenon Cieslak, Rebecca Sherlock, Wendy Yee, Khalid Aziz, Jennifer Toye, Carlos Fajardo, Zarin Kalapesi, Koravangattu Sankaran, Sibasis Daspal, Mary Seshia, Ruben Alvaro, Amit Mukerji, Orlando da Silva, Chuks Nwaesei, Kyong‐Soon Lee, Michael Dunn, Brigitte Lemyre, Kimberly Dow, Ermelinda Pelausa, Keith J. Barrington, Christine Drolet, Martine Claveau, Marc Beltempo, Valérie Bertelle, Édith Massé, Roderick Canning, Hala Makary, Cecil Ojah, Luis Monterrosa, Akhil Deshpandey, Jehier Afifi, Andrzej Kajetanowicz, Sture Andersson, Outi Tammela, Ulla Sankilampi, Timo Saarela, Eli Heymann, Shmuel Zangen, Tatyana Smolkin, Francis B. Mimouni, David Bader, Avi Rothschild, Zipora Strauss, Clari Felszer, Hussam Omari, Smadar Even Tov‐Friedman, Benjamin Bar‐Oz, Michaël Feldman, Nizar Saad, Orna Flidel‐Rimon, Meir Weisbrod, Daniel Lubin, Ita Litmanovitz, Amir Kugelman, Eric S. Shinwell, Gil Klinger, Yousif Nijim, Alona Bin‐Nun, Agneta Golan, Dror Mandel, Vered Fleisher‐Sheffer, David Kohelet, Lev Bakhrakh, Satoshi Hattori, Masaru Shirai, Toru Ishioka, Toshihiko Mori, Takasuke Amizuka, Toru Huchimukai, Hiroshi Yoshida, Ayako Sasaki, Junichi Shimizu, Toshihiko Nakamura, Mami Maruyama, Hiroshi Matsumoto, Shinichi Hosokawa, Atsuko Taki, Machiko Nakagawa, Kyone Ko, Azusa Uozumi, Setsuko Nakata, Akira Shimazaki, Tatsuya Yoda, Osamu Numata, Hiroaki Imamura, Azusa Kobayashi, Shuko Tokuriki, Yasushi Uchida, Takahiro Arai, Mitsuhiro Ito, Kuniko Ieda, Toshiyuki Ono, Masashi Hayashi, Kanemasa Maki, Mie- Toru Yamakawa, Masahiko Kawai, Noriko Fujii, Kozue Shiomi, Koji Nozaki, Hiroshi Wada, Taho Kim, Yasuyuki Tokunaga, Akihiro Takatera, T Oshima, Hiroshi Sumida, Yae Michinomae, Yoshio Kusumoto, Seiji Yoshimoto, Takeshi Morisawa, Tamaki Ohashi, Yukihiro Takahashi, Moriharu Sugimoto, Noriaki Ono, Shinichiro Miyagawa, Takahiko Saijo, Takashi Yamagami, Kosuke Koyano, Shoko Kobayashi, Takeshi Kanda, Yoshihiro Sakemi, Mikio Aoki, Koichi Iida, Mitsushi Goshi, Yuko Maruyama, Jiri Kofron, Katarina Strand Brodd, Andreas Odlind, Lars Alberg, Sofia Arwehed, Ola Hafström, Anna Kasemo, Karin Nederman, Lars Åhman, Fredrik Ingemarsson, Henrik Petersson, Pernilla Thurn, Eva Albinsson, Bo Selander, Thomas Abrahamsson, Ingela Heimdahl, Kristbjörg Sveinsdóttir, Erik Wejryd, Anna Hedlund, Maria Katarina Söderberg, Lars Navér, Thomas Brune, Jens Bäckström, Johan Robinson, Aijaz Farooqi, Erik Normann, Magnus Fredriksson, Anders Palm, Urban Rosenqvist, Bengt Walde, Cecilia Hagman, Andreas Ohlin, Rein Florell, Agneta Smedsaas Löfvenberg, Philipp Meyer, Rachel Kusche, Sven Schulzke, Mathias Nelle, Bendicht Wagner, Thomas Riedel, Grégoire Kaczala, Riccardo Pfister, Jean‐François Tolsa, Matthias Roth, Martin Stocker, Bernhard Laubscher, Andreas Malzacher, John P. Micallef, Lukas Hegi, Romaine Arlettaz, Vera Bernet

Bibliographic record

VenueThe Journal of Pediatrics · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Conditions and Treatments
Canadian institutionsPublic Health OntarioUniversity of TorontoMount Sinai Hospital
FundersCanadian Institutes of Health ResearchTerveyden ja hyvinvoinnin laitosMinisterio de Sanidad, Consumo y Bienestar SocialMinistry of Health, British ColumbiaSocialdepartementetMinistry of Health, Labour and WelfareOntario Ministry of Health and Long-Term Care
KeywordsMedicineDuctus arteriosusNeonatal intensive care unitPediatricsIntensive care medicineCardiology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.367

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 communication0.0000.000
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 head0.066
GPT teacher head0.287
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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".

Quick stats

Citations35
Published2020
Admission routes2
Has abstractno

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