{"id":"W4380884856","doi":"10.1016/j.chemolab.2023.104896","title":"A key review on graph data science: The power of graphs in scientific studies","year":2023,"lang":"en","type":"review","venue":"Chemometrics and Intelligent Laboratory Systems","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":46,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"University of Alberta","keywords":"Computer science; Visualization; Theoretical computer science; Graph drawing; Data science; Power graph analysis; Data visualization; Graph; Biological network; Popularity; Data mining; Mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.007348974,0.0004655312,0.002287428,0.003142361,0.0002592022,0.0002823242,0.002098504,0.00008057158,0.00001612525],"category_scores_gemma":[0.0004428457,0.0002857086,0.000269011,0.03337639,0.0008816074,0.000176211,0.0009807863,0.0004600573,0.00002309761],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009948598,"about_ca_system_score_gemma":0.0004488546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004333137,"about_ca_topic_score_gemma":0.000003112222,"domain_scores_codex":[0.9959397,0.000250444,0.001487945,0.001042475,0.0008748936,0.000404507],"domain_scores_gemma":[0.9950589,0.0006956155,0.001045838,0.002323494,0.0007735112,0.0001026205],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003942834,0.0005461617,0.0006703278,0.1297097,0.002521755,0.00001110155,0.0005923379,0.000007814448,0.000003291493,0.08433038,0.09377254,0.6878307],"study_design_scores_gemma":[0.00002849043,0.00004036724,0.000002131654,0.04779623,0.0004194754,4.958339e-7,0.0004119973,0.0000309132,0.00000848049,0.0002730614,0.9506848,0.000303525],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00006000873,0.9971207,0.00003221272,0.00001054499,0.0006698949,0.001333692,0.0004188386,0.00003416016,0.0003199825],"genre_scores_gemma":[0.001087068,0.9983451,0.00001247725,0.00001361414,0.00007848768,0.000163461,0.0001384696,0.00004153858,0.0001198192],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.8569123,"threshold_uncertainty_score":0.9999595,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1935248088716802,"score_gpt":0.4191072682058974,"score_spread":0.2255824593342172,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}