{"id":"W7015712645","doi":"","title":"Towards Machine Learning on Temporal Graphs","year":2025,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Advanced Graph Neural Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; McGill University; Canadian Institute for Advanced Research","keywords":"Constructive; Database transaction; Graph; Uncountable set","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","sts","research_integrity"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.000752481,0.001294657,0.001090264,0.001192512,0.001789298,0.0002803363,0.003058124,0.001001763,0.00006360439],"category_scores_gemma":[0.0006397929,0.00133092,0.0007400165,0.002509006,0.0000554271,0.001344364,0.0005325244,0.00465573,0.0001934589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004547997,"about_ca_system_score_gemma":0.0001022443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002399455,"about_ca_topic_score_gemma":0.0009000552,"domain_scores_codex":[0.993412,0.000609607,0.001092143,0.002307793,0.001361956,0.001216476],"domain_scores_gemma":[0.9962021,0.0003962253,0.0008428273,0.001697035,0.000414618,0.0004471937],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001552591,0.000155619,0.00004876614,0.0001828411,0.0001525629,0.0002087487,0.000006931927,0.001144679,0.001322274,0.4819126,0.00001715782,0.5146926],"study_design_scores_gemma":[0.003184149,0.001682305,0.002183898,0.002894487,0.000308072,0.00008370291,0.0001031836,0.008054954,0.05620555,0.5873579,0.3320807,0.005861052],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5002001,0.002784501,0.0001889677,0.0002571031,0.01560643,0.00303377,0.0009937685,0.005638492,0.4712969],"genre_scores_gemma":[0.9576721,0.0006517914,0.01051635,0.00108018,0.00007406918,0.0002098458,0.00146435,0.0002312867,0.0281],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5088316,"threshold_uncertainty_score":0.9999805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01596847993017972,"score_gpt":0.2508126400008703,"score_spread":0.2348441600706906,"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."}}