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Record W4406288554 · doi:10.1111/csp2.13135

Issue Information

2025· paratext· en· W4406288554 on OpenAlexfundno aff

Bibliographic record

VenueConservation Science and Practice · 2025
Typeparatext
Languageen
FieldEngineering
TopicHuman auditory perception and evaluation
Canadian institutionsnot available
FundersWageningen University and ResearchNational Oceanic and Atmospheric AdministrationOffice Français de la BiodiversitéNational Marine Fisheries ServiceUniversity of South AfricaUniversidad de ConcepciónHumboldt-Universität zu BerlinNature Conservancy of CanadaUniversidad San Francisco de QuitoUniversidade Federal de Minas GeraisUniversity of WaterlooSapienza Università di RomaUniversität WienConsejo Nacional de Investigaciones Científicas y TécnicasUniversity of MontanaChinese Academy of SciencesUniversity of OtagoUniversity of CanberraNational University of SingaporeUniversity of PretoriaUniversità degli Studi dell'InsubriaYale-NUS CollegeUniversity of AberdeenUniversity of ExeterU.S. Geological SurveyTrent UniversityHohai UniversityDeakin UniversityColorado State UniversityUniversity of Hawai'iMonash UniversityBoise State UniversityNorthern Arizona UniversityNature ConservancyCollege of Engineering, Michigan State UniversityUniversity of WashingtonWildlife Conservation SocietyHelsingin YliopistoMichigan State UniversityUniversity of California, DavisArizona State UniversityYale University
KeywordsPolitical science

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)0.001
metaresearch head score (Gemma)0.008
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 score0.068
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0020.001
Scholarly communication0.0060.003
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.9320.854

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 head0.354
Teacher spread0.307 · 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

Citations0
Published2025
Admission routes1
Has abstractno

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