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BIP! DB: A Dataset of Impact Measures for Scientific Publications

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Paper breakdownThe authors' claims, conditions and measurements, as JSON Signed receiptProof this review has not been altered
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Thanasis Vergoulis, Ilias Kanellos, Claudio Atzori, Andrea Mannocci, Serafeim Chatzopoulos, Sandro La Bruzzo, Natalia Manola, Paolo Manghi

Digital Libraries · Submitted 28 Jan 2021

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim DB, an open dataset that contains a variety of impact measures calculated for a large collection of more than 100 million scientific publications from various disciplines.

how it is stated · asserted 0.99 read the record →

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arXiv ID2101.12001 (version 2)
Pith IDL2M5HOZZ, Pith's permanent record of this paper and its review
CitationAndrea Mannocci, Claudio Atzori, Ilias Kanellos, Natalia Manola, Paolo Manghi, Sandro La Bruzzo, Serafeim Chatzopoulos, Thanasis Vergoulis. "BIP! DB: A Dataset of Impact Measures for Scientific Publications." arXiv:2101.12001 (2021). https://pith.science/paper/L2M5HOZZ
Claim paper

The compiled record

The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

Open the compiled record

Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-09-23: 1 request, 3,496 input tokens.

What the abstract itself states, as probabilities: claims first 0.05 · states limitation 0.05 · human participants 0.03 · controlled comparison 0.02 · randomized assignment 0.01 · states quantitative result 0.88 · compares with prior results 0.04 · mentions code or data availability 0.92.

The abstract, sentence by sentence

arXiv listing abstract v2. Results and the main claim are underlined; .

The growth rate of the number of scientific publications is constantly increasing, creating important challenges in the identification of valuable research and in various scholarly data management applications, in general. In this context, measures which can effectively quantify the scientific impact could be invaluable. In this work, we present BIP! DB, an open dataset that contains a variety of impact measures calculated for a large collection of more than 100 million scientific publications from various disciplines.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 The growth rate of the number of scientific publications is constantly increasing, creating important challenges in the identification of valuable research and in various scholarly data management applications, in general. background 1.00 0.05 0.04 asserted 1.00
s1 In this context, measures which can effectively quantify the scientific impact could be invaluable. background 0.96 0.05 0.08 hedged possibility 0.99
s2 In this work, we present BIP! contribution 1.00 0.86 0.09 asserted 0.94
s3 DB, an open dataset that contains a variety of impact measures calculated for a large collection of more than 100 million scientific publications from various disciplines. contribution 0.98 0.90 0.22 asserted 0.99

What kind of paper the classifier reports this is: dataset or benchmark 1.00 · evidence from analysis of existing data 0.73.

What was examined, and what was not

sources read
  • arXiv listing abstract v2
not examined
  • full text
  • figures and tables
  • references and citing sentences
  • relations to other papers
levels run
  • P abstract
not run
  • S sections
  • T body sentences
  • C citations
  • R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

The growth rate of the number of scientific publications is constantly increasing, creating important challenges in the identification of valuable research and in various scholarly data management applications, in general. In this context, measures which can effectively quantify the scientific impact could be invaluable. In this work, we present BIP! DB, an open dataset that contains a variety of impact measures calculated for a large collection of more than 100 million scientific publications from various disciplines.

Human review

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How the literature uses it

What this paper does with the arXiv papers it cites

Each citing sentence is taken from the citing paper's LaTeX source and typed by Pith's classifier. A label appears at probability 0.8 or more (0.95 for support), a contest at 0.7 or more; the quoted words are the citing authors'. How each label was checked · JSON

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