{"id":"W3203331145","doi":"10.48550/arxiv.2110.00577","title":"Reconstruction for Powerful Graph Representations","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Graph Neural Networks","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Expressive power; Scalability; Computer science; Leverage (statistics); Theoretical computer science; Graph; Artificial intelligence","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":[0.001147246,0.0009562042,0.0005743057,0.001048093,0.0005160524,0.001329047,0.002099816,0.00116821,0.004593755],"category_scores_gemma":[0.008624936,0.0005250481,0.001163422,0.0009020099,0.001606409,0.005450032,0.002386266,0.00282929,0.001218735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001304774,"about_ca_system_score_gemma":0.0007048512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00194527,"about_ca_topic_score_gemma":0.004398277,"domain_scores_codex":[0.9989969,0.0003050351,0.00005138463,0.0003284565,0.0002397687,0.00007848727],"domain_scores_gemma":[0.9974891,0.001154089,0.0001821743,0.0009037239,0.0002009012,0.00006991689],"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":[0.0001808377,0.000115217,0.00219028,0.0005270857,0.00009971598,0.0002178787,0.0003345142,0.4643447,0.01125722,0.266353,0.01218223,0.2421974],"study_design_scores_gemma":[0.00001627167,0.00003525123,0.000207074,0.00003468314,0.00001884047,0.00008887533,0.00005750565,0.7493539,0.003157335,0.2418351,0.005183121,0.00001198674],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05092387,0.0006159544,0.9353163,0.001561766,0.00008844221,0.00009183581,0.0008648277,0.003218282,0.007318777],"genre_scores_gemma":[0.5873669,0.0009871728,0.398686,0.000972021,0.0001228008,0.0002881349,0.00371593,0.0007624016,0.007098615],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004593755,"threshold_uncertainty_score":0.01536769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06471616162971469,"score_gpt":0.2085219120755669,"score_spread":0.1438057504458522,"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."}}