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Submissions (14)
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☐ Name Title File Grammar BETA AI Score Similarity Paper ID Actions
☐ml basicsthesis📄 ml_basics.pdf72%3%7%4918207⇩ 🗑
☐cloud rptpaper📄 cloud.docx68%89%71%4915890⇩ 🗑
☐iot surveydraft📄 iot_v2.pdfNA0%45%4912441⇩ 🗑
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◈ DrillBit
Paper ID: 4821056    Author Name: Rohit K    Submission Date: 2026-02-08 11:20
Title: Machine Learning Fundamentals
Machine Learning: Transforming Data into Knowledge
Machine Learning is no longer just a theoretical concept studied in academic labs. From voice assistants to recommendation engines, ML has quietly woven itself into the fabric of digital society. It represents humanity's effort to build systems that can learn, adapt, and make predictions.
22%
Similarity
Matched sources (5)
Excluded (0)
1
medium.com
4%
2
springer.com
3%
3
researchgate.net
3%
◈ DrillBit
Paper ID: 4918207    Author Name: Aarti N    Submission Date: 2026-02-10 09:15
Title: Data Structures Review
Modern data structures form the foundation of efficient software systems. From hash tables to balanced trees, each structure offers unique trade-offs between time and space complexity. Understanding these trade-offs is critical.

Arrays provide constant-time access but lack flexibility for insertions. Linked lists offer dynamic sizing but sacrifice random access speed.
38%
AI
The DrillBit AI model identifies AI generated text from tools like ChatGPT.
It gives a percentage estimate of AI content and highlights the sections.
◈ DrillBit
Paper ID: 4918207    Author Name: Aarti N    Submission Date: 2026-02-10 09:15
Detailed Analysis
Submitted Text
Characters
5120
Words
842
Sentences
56
Lines
74
1. Phrases Quality
Unique Words
61.45%
Rare Words
38.92%
Common Words
48.70%
74%
Grammar
1. Phrases Quality:79%
2. Non-Duplicate:100%
3. Indexed Content:12%
4. Grammar Info:97%
Grammar Info: Evaluates grammatical accuracy including spelling, punctuation, and tense.
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Leia os resultados das suas submissões

Uma visita guiada rápida - percorrer a tabela de submissões e abrir os relatórios de semelhança, IA e gramática. Clique em reproduzir para a ver como um pequeno vídeo.

Aceda a «A minha pasta», selecione uma pasta e clique no nome da pasta ou no ícone seguinte para visualizar os ficheiros enviados. Cada envio apresenta informações detalhadas, incluindo pontuações de gramática, IA e similaridade.

Tabela de envios e ações em massa

Dentro de uma pasta, cada submissão apresenta: Nome, Título, Ficheiro, Idioma, Pontuação de Gramática, Pontuação de IA, Similaridade, ID do Artigo, Data de Submissão e Ações. Selecione vários ficheiros para operações em massa.

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Dashboard › My folder › NLP Research
Submissions (14)
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☐ Name ↑ Title ↑ File ↑ Lang.. ↑ Grammar BETA AI Score Similarity Pap.. ↑ Submis.. ↑ Actions
☐ img conv.. report 📄 scan.pdf English NA NA ⚠ 0% 4921035 12-03-26.. ⇩ 🗑
☐ ml basics.. thesis 📄 updated.. English 72% 3% 7% 4918207 10-03-26.. ⇩ 🗑
☐ cloud rpt.. paper 📄 cloud.docx English 68% 89% 71% 4915890 08-03-26.. ⇩ 🗑
☐ iot survey.. draft 📄 iot_v2.pdf English NA 0% 45% 4912441 05-03-26.. ⇩ 🗑
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Similarity report
Summary report
Grammar report
AI report
Document Error: 1) Document is Corrupted/Encrypted 2) Document is in Image Format 3) Document does not have minimum 50 words 4) Document contains hidden characters
Bulk actions: Select multiple checkboxes to see Save to Repository, Bulk Report Download, and Delete options at the top.
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Submissions table & bulk actions

View all submission details. Select checkboxes for bulk Save, Download, or Delete operations.

Detalhes do envio

Ações em massa

Selecione vários envios utilizando as caixas de seleção para aceder a: Guardar no repositório, Transferência em massa do relatório (ZIP) e Eliminação em massa. Estas opções só aparecem quando as caixas de seleção estão marcadas.

Página de análise - guia passo a passo completo

Clique numa percentagem de semelhança para abrir o relatório de análise. A barra de ferramentas disponibiliza funcionalidades para partilhar, descarregar, guardar e configurar o relatório.

◈ DrillBit
Paper ID: 4821056    Author Name: Rohit K    Submission Date: 2026-02-08 11:20:45
1
2
3
Title: Machine Learning Fundamentals
Machine Learning: Transforming Data into Knowledge
Introduction
Machine Learning (ML) is no longer just a theoretical concept studied in academic labs-it has become an integral part of modern technology. From voice assistants to recommendation engines, ML has quietly woven itself into the fabric of digital society. While many see ML as a subset of AI, it represents humanity's effort to build systems that can learn, adapt, and make predictions.

A Brief History of M...
Total Pages: 3Word Count: 2840
AI score 2% > Grammar 68% >
● Satisfactory (0-10%) ● Upgrade (11-40%) ● Poor (41-60%) ● Unacceptable (61-100%)
22%
Similarity
Matched sources (5)
Excluded sources (0)
☐   Primary SourceExclude
☐1
medium.com
Internet Data
4%
>
☐2
springer.com
Publication
3%
>
☐3
researchgate.net
Internet Data
3%
>
☐4
ieee.org
Internet Data
2%
>
☐5
acm.org
Internet Data
2%
>
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Submission Details
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Folder NameNLP Research
Date & Time2026-02-08 11:20
Paper Id4821056
File Nameml_basics.pdf
Word Count2840
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Rohit Kumar
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ML Fundamentals
Published Year *
2026
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Analysis page - full walkthrough

Toolbar features, score ranges, matched sources, download, share, and more options.

Relatório de IA

A pontuação de IA ajuda a identificar secções que possam ter sido criadas com ferramentas de IA. As secções assinaladas são destacadas a ciano, com uma percentagem que indica a probabilidade de se tratar de conteúdo gerado por IA.

◈ DrillBit
Paper ID: 4918207    Author Name: Aarti N    Submission Date: 2026-02-10 09:15:30
Title: Data Structures Review
Modern data structures form the foundation of efficient software systems. From hash tables to balanced trees, each structure offers unique trade-offs between time and space complexity. Understanding these trade-offs is critical for building performant applications.

Arrays provide constant-time access but lack flexibility for insertions. Linked lists offer dynamic sizing but sacrifice random access speed. Graph structures enable modeling of complex relationships.

The choice of data structure depends on the specific use case. For real-time systems, priority queues and heaps ensure efficient scheduling. For search-heavy applications, binary search trees and tries provide logarithmic lookup times.

Advanced structures like B-trees power database indexing. Bloom filters enable probabilistic membership testing with minimal memory usage, making them ideal for large-scale distributed systems.
Similarity Score 8% >
38%
AI
The DrillBit AI detection model identifies AI generated text from tools like ChatGPT.
It provides a percentage estimation of AI content and highlights specific sections.
DrillBit AI model serves as a preliminary indicator of AI generated text within a document.
Interactive guide

AI detection report

Cyan highlighted sections indicate AI-generated content. The percentage shows the estimated AI content ratio.

Relatório gramatical

A Pontuação Gramatical reflete a qualidade da redação através de quatro métricas principais: Qualidade das frases, Conteúdo não duplicado, Conteúdo indexado e Informações gramaticais.

◈ DrillBit
Paper ID: 4918207    Author Name: Aarti N    Submission Date: 2026-02-10 09:15:30
Title: Data Structures Review
Detailed Analysis
Submitted Text
Characters
5120
Words
842
Sentences
56
Lines
74
Reading and Execution Time
Reading
0 Hr, 3 Min
Speaking
0 Hr, 6 Min
Execution
0 Hr, 1 Min
1. Phrases Quality
Only Alphabets
83.20%
Only Numbers
00.15%
Alpha-numeric
00.48%
Special Chars.
16.17%
Unique Words   61.45%
Rare Words   38.92%
Common Words   48.70%
Word Length   05.83
Measures average word length (Characters per word).
Sentence Length   14.25
Measures average sentence length (words per sentence).
2. Non-Duplicate Content
3. Indexed content
Sl. NoIndexLinesWords% in Report
1Other Data74842100.0%view

Submitted Text:
Line 1| Data Structures: A Foundation for Efficient Computing
Line 2| Introduction Modern software systems rely heavily on well-designed
Line 3| data structures to manage, organize, and retrieve information
Line 4| efficiently. From simple arrays to complex graph algorithms,
Line 5| understanding data structures is essential for building scalable
Line 6| applications that perform well under varying workloads.
Similarity Score 8% >
74%
Grammar
1. Phrases Quality:79%
2. Non-Duplicate Content:100%
3. Indexed Content:12%
4. Grammar Info:97%
Phrases Quality: Measures language effectiveness benchmarked against academic standards.
Non-Duplicate Content: Evaluates originality by identifying repetitive content.
Indexed Content: Measures structural quality and inclusion of essential sections.
Grammar Info: Evaluates grammatical accuracy including spelling, punctuation, and tense.
Interactive guide

Grammar report & detailed analysis

View Phrases Quality, Non-Duplicate Content, Indexed Content, and Grammar Info metrics.

Intervalos da pontuação de similaridade

Transferências de relatórios

Estão disponíveis quatro tipos de relatório na coluna «Ações»: Relatório de Similaridade, Relatório de Resumo, Relatório Gramatical e Relatório de IA.

Erro no documento: Se um ficheiro apresentar ⚠ 0% na coluna «Semelhança», isso indica um erro no documento. Consulte o guia «Erros no documento» para obter mais detalhes.
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