{"id":"W4392384843","doi":"10.1145/3616855.3635694","title":"Temporal Graph Analysis with TGX","year":2024,"lang":"en","type":"article","venue":"","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Fonds de recherche du Québec – Nature et technologies; Samsung; Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research","keywords":"Computer science; Python (programming language); Graph; Node (physics); Data mining; Theoretical computer science; Programming language","routes":{"ca_aff":true,"ca_fund":true,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0000730364,0.0001021506,0.0001718691,0.0002677191,0.00004110967,0.0001195721,0.0000982718,0.00001117662,0.00353267],"category_scores_gemma":[1.485045e-7,0.00006909417,0.0002093846,0.002105799,0.00002633971,0.00007782467,0.00002744415,0.00007947925,0.00003651793],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000702815,"about_ca_system_score_gemma":0.00002012827,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008409978,"about_ca_topic_score_gemma":0.0001681352,"domain_scores_codex":[0.9993957,0.00001463085,0.0001178748,0.000221687,0.0001132923,0.0001367793],"domain_scores_gemma":[0.9996581,0.00002338203,0.00001808264,0.0002303749,0.00002665668,0.00004340348],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007155561,0.00007334635,0.6332294,0.000007493757,0.006573494,0.00001101837,0.0000762261,0.0005848753,0.00004968451,0.3078052,0.02603582,0.02554625],"study_design_scores_gemma":[0.0006658835,0.0004036596,0.04574736,0.0001505561,0.01790755,0.000003581204,0.0009742547,0.279923,0.005500691,0.2312182,0.4147662,0.002739049],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06210244,0.0001186002,0.801901,0.000207383,0.00002076746,0.00008879315,0.00001043815,0.0005112812,0.1350393],"genre_scores_gemma":[0.9917567,7.794412e-7,0.005011087,0.00002007807,0.0001200209,0.00001636621,0.00006913022,0.00001056031,0.002995234],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9296543,"threshold_uncertainty_score":0.9973782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006143539471746161,"score_gpt":0.250863628545124,"score_spread":0.2447200890733778,"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."}}