{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001357929,0.001291215,0.001045904,0.0008536601,0.0004517154,0.0007519686,0.003059464,0.0016271,0.001718826],"category_scores_gemma":[0.004677607,0.0006013082,0.0006226585,0.0009372847,0.001203639,0.002579088,0.002222714,0.002301107,0.0007491926],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001152236,"about_ca_system_score_gemma":0.00105007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00698766,"about_ca_topic_score_gemma":0.01220982,"domain_scores_codex":[0.9992029,0.0002132653,0.00002606009,0.0003147529,0.0001647561,0.00007824954],"domain_scores_gemma":[0.9987227,0.0004497918,0.0001462979,0.0003385007,0.0002513629,0.00009135438],"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":[0.0002260419,0.0001747646,0.002108075,0.0001389688,0.0001044113,0.0001280983,0.00007842277,0.7251517,0.003899452,0.01632674,0.007141151,0.2445222],"study_design_scores_gemma":[0.000005648773,0.00001997101,0.00009808339,0.000004186601,0.000004949643,0.0000136987,0.000004628453,0.990146,0.0005626727,0.008730759,0.0004055351,0.000003880313],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02359513,0.0004282366,0.9713713,0.0003592447,0.00009821935,0.00008545506,0.0002522488,0.002165691,0.001644586],"genre_scores_gemma":[0.6289887,0.0004857651,0.3605213,0.0006853702,0.0001275836,0.0002444821,0.002058473,0.0003384181,0.006549831],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00698766,"threshold_uncertainty_score":0.01389396,"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."}}