{"id":"W4388340544","doi":"10.1007/978-3-031-46674-8_33","title":"Towards Time-Variant-Aware Link Prediction in Dynamic Graph Through Self-supervised Learning","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Graph Neural Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Interpretability; Theoretical computer science; Graph; Embedding; Graph embedding; Feature learning; Artificial intelligence; Machine learning","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":[0.0007819608,0.0008899694,0.001481136,0.001347231,0.0004363219,0.001024542,0.002489913,0.001391865,0.001561772],"category_scores_gemma":[0.003015909,0.0005679471,0.0008053048,0.001837129,0.0006348339,0.002250401,0.001452567,0.001606575,0.001113227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005336242,"about_ca_system_score_gemma":0.0006605752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005971775,"about_ca_topic_score_gemma":0.009521492,"domain_scores_codex":[0.999461,0.0001046966,0.00002285702,0.0002331999,0.0001207078,0.00005758956],"domain_scores_gemma":[0.998061,0.001058473,0.0001655996,0.0003559091,0.0002659478,0.0000930926],"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":[0.0001850669,0.0002795154,0.001671056,0.0001356304,0.0001633651,0.0001410776,0.00009987488,0.6186264,0.007597812,0.009720794,0.00942054,0.3519589],"study_design_scores_gemma":[0.000001708606,0.000005461284,0.00005824043,0.000001884452,0.000003616856,0.000007923565,0.00000272379,0.9967913,0.0002820114,0.002713546,0.0001293832,0.00000214232],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02035647,0.0004377245,0.975679,0.0001454431,0.00007157872,0.00002649489,0.0002430625,0.002037924,0.001002314],"genre_scores_gemma":[0.5958527,0.0005881337,0.3924024,0.0003051573,0.0003068001,0.000105813,0.002125464,0.0006122771,0.007701268],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005971775,"threshold_uncertainty_score":0.01187408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.012310496478237,"score_gpt":0.2390525024103609,"score_spread":0.2267420059321239,"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."}}