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Record W4389765048 · doi:10.53555/sfs.v10i1.1875

An examination of the functional analysis of Bank of Baroda with a focus on financial parameters

2023· article· en· W4389765048 on OpenAlexvenueno aff
Mr. Sunny Masand

Bibliographic record

VenueJournal of Survey in Fisheries Sciences · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIslamic Finance and Banking Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBalance sheetAsset qualityProfitability indexReturn on equityBusinessReturn on assetsFinanceSafeguardingFinancial systemBank statementEquity ratioEquity (law)Profit (economics)Financial analysisFinancial institutionEconomicsCapital adequacy ratio

Abstract

fetched live from OpenAlex

Banking involves safeguarding money on behalf of others. Banks lend this money, earning interest that contributes to profits for both the bank and its customers. A bank is a licensed financial institution that accepts deposits and extends loans. This study aims to assess the performance of Bank of Baroda over the past five years (2016-2021) using ratio analysis techniques. The analysis provides valuable insights into the financial strength of the bank in terms of Asset Quality, Management Efficiency, and Earning Ratios. Ratios are derived from a thorough examination of the bank's Balance Sheet and Profit and Loss Account. Bank of Baroda has demonstrated an improvement in its financial performance in recent quarters, evident through increasing net profits and enhanced asset quality. Profitability ratios, including return on assets and return on equity, have seen positive developments, indicating that the bank is generating more profit from its assets and equity

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.089
GPT teacher head0.240
Teacher spread0.151 · 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 designObservational
Domainnot available
GenreEmpirical

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
Published2023
Admission routes1
Has abstractyes

Explore more

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