{"id":"W4399765342","doi":"10.1101/2024.06.17.599219","title":"Path-based reasoning for biomedical knowledge graphs with BioPathNet","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Graph Neural Networks","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research; HEC Montréal; Université de Montréal; Mila - Quebec Artificial Intelligence Institute; Cegep Edouard Montpetit","funders":"Bundesministerium für Bildung und Forschung; National Institutes of Health; Joachim Herz Stiftung","keywords":"Path (computing); Knowledge graph; Computer science; Artificial intelligence; Data science; Programming language","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001156752,0.001188083,0.0005088984,0.003063076,0.0006370315,0.00139496,0.001443086,0.001215768,0.006140307],"category_scores_gemma":[0.008105,0.0005118574,0.001444,0.001513608,0.000668987,0.002827502,0.001485224,0.001692096,0.000963927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001668036,"about_ca_system_score_gemma":0.001674396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01396166,"about_ca_topic_score_gemma":0.02628577,"domain_scores_codex":[0.9993863,0.000155941,0.00005471382,0.0002249052,0.0001500438,0.00002818468],"domain_scores_gemma":[0.9972383,0.001865281,0.0002228778,0.0002787036,0.0003205198,0.00007429384],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001950922,0.0001586065,0.003755749,0.001136937,0.0001808547,0.0006149315,0.0003894902,0.5633383,0.0035856,0.08563313,0.02322845,0.3177829],"study_design_scores_gemma":[0.00002253791,0.00002408705,0.0002266107,0.00007038594,0.00003454196,0.00006350246,0.00003731537,0.9074649,0.001586475,0.08022683,0.01023137,0.00001134377],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01689561,0.0009597106,0.9601516,0.001492091,0.0001787334,0.0002355971,0.007535861,0.009092078,0.003458794],"genre_scores_gemma":[0.2881097,0.001379503,0.6850004,0.0009444104,0.00011644,0.0005903469,0.01978108,0.0005394808,0.003538702],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01396166,"threshold_uncertainty_score":0.0277608,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01147742921684764,"score_gpt":0.2321011121363298,"score_spread":0.2206236829194822,"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."}}