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Record W2995217039 · doi:10.1186/s40643-019-0286-0

CAZymes-based ranking of fungi (CBRF): an interactive web database for identifying fungi with extrinsic plant biomass degrading abilities

2019· article· en· W2995217039 on OpenAlex
Ayyappa Kumar Sista Kameshwar, Luiz Pereira Ramos, Wensheng Qin

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBioresources and Bioprocessing · 2019
Typearticle
Languageen
FieldEngineering
TopicBiofuel production and bioconversion
Canadian institutionsLakehead University
FundersNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsBiologyRanking (information retrieval)Web pageComputer scienceDatabaseWorld Wide WebJavaScriptInformation retrieval

Abstract

fetched live from OpenAlex

Abstract Carbohydrate-active enzymes (CAZymes) are industrially important enzymes, which are involved in synthesis and breakdown of carbohydrates. CAZymes secreted by microorganisms especially fungi are widely used in industries. However, identifying an ideal fungal candidate is costly and time-consuming process. In this regard, we have developed a web-database “CAZymes Based Ranking of Fungi (CBRF)”, for sorting and selecting an ideal fungal candidate based on their genome-wide distribution of CAZymes. We have retrieved the complete annotated proteomic data of 443 published fungal genomes from JGI-MycoCosm web-repository, for the CBRF web-database construction. CBRF web-database was developed using open source computing programing languages such as MySQL, HTML, CSS, bootstrap, jQuery, JavaScript and Ajax frameworks. CBRF web-database sorts complete annotated list of fungi based on three selection functionalities: (a) to sort either by ascending (or) descending orders; (b) to sort the fungi based on a selected CAZy group and class; (c) to sort fungi based on their individual lignocellulolytic abilities. We have also developed a simple and basic webpage “S-CAZymes” using HTML, CSS and Java script languages. The global search functionality of S-CAZymes enables the users to understand and retrieve information about a specific carbohydrate-active enzyme and its current classification in the corresponding CAZy family. The S-CAZymes is a supporting web page which can be used in complementary with the CBRF web-database (knowing the classification of specific CAZyme in S-CAZyme and use this information further to sort fungi using CBRF web-database). The CBRF web-database and S-CAZymes webpage are hosted through Amazon ® Web Services (AWS) available at http://13.58.192.177/RankEnzymes/about . We strongly believe that CBRF web-database simplifies the process of identifying a suitable fungus both in academics and industries. In future, we intend to update the CBRF web-database with the public release of new annotated fungal genomes.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.151
Threshold uncertainty score0.743

Codex and Gemma teacher scores by category

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

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 head0.021
GPT teacher head0.236
Teacher spread0.215 · 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