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Record W4399710567 · doi:10.3791/66848-v

JoVE Video Dataset

2024· article· pt· W4399710567 on OpenAlexafffund
Claudia Banchini, Franck Stefani

Bibliographic record

Venuenot available
Typearticle
Languagept
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Arbuscular mycorrhizal (AM) fungi are difficult to manipulate and observe due to their permanent association with plant roots and propagation in the rhizosphere. Typically, AM fungi are cultured under in vivo conditions in pot culture with an autotrophic host or under in vitro conditions with Ri Transfer-DNA transformed roots (heterotrophic host) in a Petri dish. Additionally, the cultivation of AM fungi in pot culture occurs in an opaque and non-sterile environment. In contrast, in vitro culture involves the propagation of AM fungi in a sterile, transparent environment. The superabsorbent polymer-based autotrophic system (SAP-AS) has recently been developed and shown to combine the advantages of both methods while avoiding their respective limitations (opacity and heterotrophic host, sterility). Here, we present a detailed protocol for easy preparation, single spore inoculation, and observation of AM fungi in SAP-AS. By modifying the Petri dishes, high-resolution photographic and video observations were possible on living specimens, which would have been difficult or impossible with current in vivo and in vitro techniques.

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)0.003
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.413
Threshold uncertainty score0.589

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.004
Science and technology studies0.0010.000
Scholarly communication0.0030.002
Open science0.0030.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.5870.361

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 head0.258
Teacher spread0.235 · 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
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
Published2024
Admission routes2
Has abstractyes

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