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Record W4246391215 · doi:10.1002/da.22410

Depression and Anxiety Issue Information

2016· article· en· W4246391215 on OpenAlexafffundabout
Jasmine Turna, Keren Grosman Kaplan, Rebecca Anglin, Michael Van Ameringen, Shari A. Steinman, Susanne E. Ahmari, Tse Choo, Marcia B. Kimeldorf, Rachel Feit, Sarah Loh, Victoria B. Risbrough, Mark A. Geyer, Joanna Steinglass, Melanie M. Wall, Franklin R. Schneier, Abby J. Fyer, H Simpson, Paula P. Schnurr, Carole A. Lunney, Peter Roy‐Byrne, Myrna M. Weissman, Naomi M. Simon, Rudolph Uher

Bibliographic record

VenueDepression and Anxiety · 2016
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsDalhousie University
FundersNational Institute of Mental HealthUniversity of California, Los AngelesMcMaster UniversitySchool of Medicine, Stanford UniversityUniversity of Cape TownSchool of Medicine, Emory UniversityUniversity of ReginaUniversiteit van AmsterdamRush UniversityVrije Universiteit AmsterdamUniversity of South FloridaUniversity of OxfordUniversity of PittsburghUniversity of CincinnatiUniversity of LouisvilleUniversity of WashingtonJohns Hopkins UniversityMcLean HospitalUniversity of MiamiMassachusetts General HospitalCase Western Reserve UniversityEmory UniversityBrown UniversityVirginia Commonwealth UniversityUniversity of California, San DiegoYale UniversityNew York State Psychiatric Institute
KeywordsAnxietyCitationDepression (economics)PsychologyInformation retrievalPsychiatryComputer scienceLibrary science

Abstract

fetched live from OpenAlex

US$1218 (US), US$1218 (Canada & Mexico), 623 (UK), 788 (Europe), US$1218

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.352
Threshold uncertainty score0.503

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.6480.374

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 head0.012
GPT teacher head0.279
Teacher spread0.267 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2016
Admission routes3
Has abstractyes

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