{"id":"W7019398766","doi":"","title":"Geometric deep learning: features, graphs, and affinity supervision","year":2020,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Advanced Graph Neural Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Stability (learning theory); Identification (biology); Artificial neural network; Work (physics)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003973756,0.0005291328,0.0005727898,0.0005527879,0.0003063891,0.0009032896,0.001107256,0.0008136894,0.005701654],"category_scores_gemma":[0.002793423,0.0003629496,0.00035483,0.0009063279,0.0006648634,0.001771403,0.001254704,0.001964065,0.002159492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007760552,"about_ca_system_score_gemma":0.0008385425,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004684005,"about_ca_topic_score_gemma":0.006849173,"domain_scores_codex":[0.9997315,0.00005157447,0.000009889715,0.00009603142,0.00008103719,0.00003001875],"domain_scores_gemma":[0.9993448,0.0001776272,0.00006715062,0.0001436056,0.0001953279,0.00007143274],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001370888,0.0001130277,0.001650534,0.0001810093,0.0000409926,0.00003219351,0.00006510838,0.09075117,0.003557605,0.0918116,0.06616573,0.7454939],"study_design_scores_gemma":[0.00002456056,0.00005237763,0.001127603,0.00005190133,0.00002444888,0.00004852244,0.00003007453,0.8180675,0.004568563,0.1607842,0.01520248,0.00001779259],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04365883,0.003923221,0.9296726,0.004003267,0.0005155072,0.00005180652,0.00111268,0.002792781,0.01426933],"genre_scores_gemma":[0.5795464,0.00460481,0.3799882,0.0007170969,0.000568689,0.0001296183,0.004484638,0.0005300064,0.02943059],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005701654,"threshold_uncertainty_score":0.01907396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01303046553968749,"score_gpt":0.2302943370639032,"score_spread":0.2172638715242157,"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."}}