{"id":"W4386688780","doi":"10.31237/osf.io/fvnh6","title":"Directional Graph Attention Network","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Advanced Graph Neural Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Graph; Attention network; Data mining; Margin (machine learning); Theoretical computer science; Artificial intelligence; Pattern recognition (psychology); 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002441944,0.0002746009,0.0002508018,0.0001699103,0.0001715211,0.0002028481,0.001207012,0.0002475703,0.00001838298],"category_scores_gemma":[0.00001578386,0.0002625865,0.0002905542,0.0008479256,0.000044901,0.0002326362,0.002493997,0.0007099828,0.0002052447],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004075141,"about_ca_system_score_gemma":0.00003934954,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002890607,"about_ca_topic_score_gemma":0.00005630958,"domain_scores_codex":[0.9978204,0.00007832544,0.0003170706,0.0009355678,0.0003993352,0.0004492935],"domain_scores_gemma":[0.9985311,0.0001450718,0.0001777797,0.0009451596,0.00009616451,0.0001047102],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000007102486,0.00004614715,0.004509128,0.00004852717,0.0001376666,0.00005804275,0.00002578341,0.5991148,0.00003734134,0.223749,0.1469273,0.02533912],"study_design_scores_gemma":[0.0001130483,0.00002327803,0.02815973,0.0001155749,0.00001153385,0.00001185006,0.000001682786,0.1213338,0.00001738618,0.8457083,0.003996287,0.0005075095],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0005091238,0.000203389,0.9829433,0.001431621,0.009409949,0.0002610142,0.000003058754,0.002349411,0.002889164],"genre_scores_gemma":[0.09401917,0.001149714,0.8644262,0.001888617,0.005038383,0.0005108093,0.0002522622,0.0001662469,0.03254859],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6219593,"threshold_uncertainty_score":0.9999827,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03509300879736632,"score_gpt":0.2725107324210038,"score_spread":0.2374177236236374,"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."}}