{"id":"W4400676476","doi":"10.1016/j.ipm.2024.103831","title":"Homogeneous graph neural networks for third-party library recommendation","year":2024,"lang":"en","type":"article","venue":"Information Processing & Management","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Homogeneous; Computer science; Graph; Third party; Artificial neural network; World Wide Web; Information retrieval; Theoretical computer science; Artificial intelligence; Internet privacy; Combinatorics; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0003258338,0.0001429155,0.0001090833,0.0003118982,0.0002139386,0.002215098,0.0004283212,0.0000541777,0.00000849676],"category_scores_gemma":[0.000002714858,0.0001247319,0.0000737875,0.0005082298,0.00001106507,0.00715573,0.0001948233,0.00009194115,0.00001542102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003332887,"about_ca_system_score_gemma":0.0000195361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002539705,"about_ca_topic_score_gemma":4.318476e-7,"domain_scores_codex":[0.998965,0.0000220398,0.0004376576,0.0001987111,0.0001477382,0.0002288459],"domain_scores_gemma":[0.9995295,0.0000283391,0.0001312194,0.0002214563,0.00004309437,0.00004640621],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003017067,0.00000906364,0.000007931631,0.0004299824,0.00001924082,0.000001570373,0.0003614743,0.0004898176,3.235435e-7,0.03513505,0.05697139,0.9065711],"study_design_scores_gemma":[0.00008948681,0.00002738838,0.00003926222,0.00008715472,0.000007955492,0.000009511847,0.00004356513,0.6496555,0.00006146517,0.007861371,0.341989,0.00012845],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00005855713,0.0002941955,0.9730971,0.003044887,0.0008510451,0.0005764747,0.000003713268,0.001609834,0.0204642],"genre_scores_gemma":[0.8010054,0.0002131766,0.1918158,0.004344475,0.0002607286,0.0009038458,0.000324741,0.00003208529,0.001099746],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9064427,"threshold_uncertainty_score":0.9988207,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01385868293302533,"score_gpt":0.2466361661788818,"score_spread":0.2327774832458565,"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."}}