Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1].
Scientific Ranking over Heterogeneous Academic Hypernetwork
Authors: Ronghua Liang, Xiaorui Jiang
AAAI 2016 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | $ + + $$3 1 + 0 0 + + + + 0 1 +* 3 # # # / - JHK + 1 ++ # + # # / # # , + + # # + , * 5 0 # / - J.K / ++ + + # + # + + # # * 0 + + # # + + , # + # * # 0 / - JH.K + 1 ++ # + + # # 1 * 5 # # + # / 1 # + + / + + / / -* " $ + + + : +H ; # # + + / 1 / / 0/ , 1 +M + G / +0 0 / + + 1 * 0 + 1 1 $$3 + 0 + + + + # # + 5 * $ + + +0 + # # / + # / / + + # + + + * 3 + " + ! : 83"!:9 ?S + ( -S S @* + : + + $ H 8:$H9 . 1 * @ # 0 + + * C 3"!: # 0 + :$H + 1 + 0 # + + + # 0 * |
| Researcher Affiliation | Academia | The provided text does not contain explicit institutional affiliations (university names, company names, or email domains) for the authors, preventing classification. It only mentions 'Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16)'. |
| Pseudocode | No | The provided text contains mathematical equations but does not include clearly labeled pseudocode or algorithm blocks. The formatting is too garbled to identify structured steps as pseudocode. |
| Open Source Code | No | The provided text does not provide concrete access to source code (specific repository link, explicit code release statement, or code in supplementary materials) for the methodology described in this paper. |
| Open Datasets | Yes | The paper mentions common public academic datasets, specifically 'DBLP' (3"!:9 ?S + ( -S S @) and 'SS3' ($$3 # # 0 # 1 + 1 $!2 8$ ! # 2 @* $$3 + + 0 / 1 *). |
| Dataset Splits | No | The provided text does not specify exact dataset split percentages, sample counts for each split, or detailed splitting methodology needed to reproduce the data partitioning. |
| Hardware Specification | No | The provided text does not provide specific hardware details (exact GPU/CPU models, processor types with speeds, memory amounts, or detailed computer specifications) used for running its experiments. |
| Software Dependencies | No | The provided text does not provide specific ancillary software details (e.g., library or solver names with version numbers) needed to replicate the experiment. |
| Experiment Setup | No | The provided text does not contain specific experimental setup details (concrete hyperparameter values, training configurations, or system-level settings) in the main text. |