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Record W6977594853 · doi:10.7479/ws8v-z270/8

Fotoexperiment zum Pflanzenwachstum | Plant Growth Photo Experiment

2022· dataset· de· W6977594853 on OpenAlexaff

Bibliographic record

VenueMuseum für Naturkunde Berlin - Leibniz-Institut für Evolutions- und Biodiversitätsforschung · 2022
Typedataset
Languagede
Field
Topic
Canadian institutionsMinnow Environmental (Canada)
Fundersnot available
KeywordsPlant growthPollinatorPollinationDevelopmental stage

Abstract

fetched live from OpenAlex

Um die Bestäuberleistung von Wildbienen zu untersuchen, wurde im Projekt Bienen, Bestäubung und Bürgerwissenschaft in Berlins Gärten das Wachstum verschiedener Pflanzen beobachtet. Hier gibt es eine Übersicht der Ergebnisse, die in Form von Fotos die verschiedenen Stadien des Wachstums zeigen. In order to investigate the pollinator performance of solitary bees, the project Bees, Pollination and Citizen Science observed the growth of various plants in Berlin's gardens. Here is an overview of the results, showing the different stages of growth in photographic form.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.038
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.004
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0380.043

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 head0.022
GPT teacher head0.290
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; 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 designBench or experimental
Domainnot available
GenreDataset

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
Published2022
Admission routes1
Has abstractyes

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