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Influence of light exposure during early life on the age of onset of bipolar disorder

2015· review· en· W2140909971 on OpenAlexaff
Michael Bauer, Tasha Glenn, Martin Alda, Ole A. Andreassen, Elias Angelopoulos, Raffaella Ardau, Christopher Baethge, Rita Bauer, Bernhard T. Baune, Frank Bellivier, Robert H. Belmaker, Michael Berk, Thomas Bjella, Letizia Bossini, Yuly Bersudsky, Eric Yat Wo Cheung, Jörn Conell, Maria Del Zompo, Seetal Dodd, Bruno Étain, Andrea Fagiolini, Mark A. Frye, Jade Garneau-Fournier, Ana González‐Pinto, John F. Gottlieb, Hirohiko Harima, Stefanie Hassel, Chantal Henry, Apostolos Iacovides, Erkki Isometsä, Flávio Kapczinski, Sebastian Kliwicki, Barbara König, Rikke Krogh, Maurício Kunz, Beny Lafer, Erik Roj Larsen, Ute Lewitzka, Carlos López‐Jaramillo, Glenda MacQueen, Mirko Manchia, Wendy Marsh, Mónica Martínez‐Cengotitabengoa, Ingrid Melle, Scott Monteith, Gunnar Morken, Rodrigo Muñoz, Fabiano G. Nery, Claire O’Donovan, Yamima Osher, Andrea Pfennig, Danilo Quiroz, Raj Ramesar, Natalie Rasgon, Andreas Reif, Philipp Ritter, Janusz Rybakowski, Kemal Sagduyu, Ângela Miranda- Scippa, Emanuel Severus, Christian Simhandl, Dan J. Stein, Sergio Strejilevich, Ahmad Hatim Sulaiman, Kirsi Suominen, Hiromi Tagata, Yoshitaka Tatebayashi, Carla Torrent, Eduard Vieta, Biju Viswanath, Mihir J. Wanchoo, Mark Zetin, Peter C. Whybrow

Bibliographic record

VenueJournal of Psychiatric Research · 2015
Typereview
Languageen
FieldNeuroscience
TopicCircadian rhythm and melatonin
Canadian institutionsUniversity of CalgaryDalhousie University
Fundersnot available
KeywordsDaylightBipolar disorderMoodInsolationCircadian rhythmSunlightDemographyMedicineInternal medicinePsychiatryClimatology

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 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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.104
GPT teacher head0.392
Teacher spread0.287 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations50
Published2015
Admission routes1
Has abstractno

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