{"id":"W3174867666","doi":"10.48550/arxiv.2106.15755","title":"Dual GNNs: Graph Neural Network Learning with Limited Supervision","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Graph Neural Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Dual (grammatical number); Computer science; Graph; Artificial neural network; Artificial intelligence; Machine learning; Theoretical computer science","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":[0.0002009745,0.000599425,0.000569081,0.0002884513,0.000447777,0.000339475,0.001701745,0.000398871,0.00002227628],"category_scores_gemma":[0.00003013729,0.0006236618,0.0003307375,0.002505241,0.000179034,0.000766432,0.003394845,0.002053294,0.00001421631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001024921,"about_ca_system_score_gemma":0.0001272353,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005542321,"about_ca_topic_score_gemma":0.0001047124,"domain_scores_codex":[0.9962375,0.0004248382,0.0002815157,0.001989103,0.0002200358,0.0008470656],"domain_scores_gemma":[0.9972325,0.0002562198,0.000338281,0.001569766,0.0002984224,0.0003048361],"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":[0.00005691882,0.00003973464,0.007722629,0.00003071909,0.00008976777,0.002276216,0.0002080062,0.9799179,0.00002000374,0.008182201,0.00009842929,0.001357441],"study_design_scores_gemma":[0.0007186172,0.0002460821,0.004769127,0.0003323255,0.00008952121,0.0000630578,0.0001282709,0.986271,0.00003087299,0.006004592,0.0003841716,0.0009623162],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6057222,0.0003509695,0.3919493,0.0001028639,0.0007105105,0.0002517912,0.000001696234,0.0005853158,0.0003252794],"genre_scores_gemma":[0.9904104,0.0005312728,0.008071748,0.0002344883,0.0002240471,0.000001613801,0.00006132075,0.00004915353,0.0004159479],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3846882,"threshold_uncertainty_score":0.9996215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04431417247660114,"score_gpt":0.1754680419533642,"score_spread":0.1311538694767631,"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."}}