{"id":"W3157770533","doi":"10.48550/arxiv.2104.12898","title":"SGNet: A Super-class Guided Network for Image Classification and Object Detection","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Nuclear Safety and Security Commission; National Aeronautics and Space Administration","keywords":"Inference; Class (philosophy); Computer science; Artificial intelligence; Object (grammar); Pattern recognition (psychology); Image (mathematics); Object detection; Exploit; Machine learning; Data mining","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001075718,0.001451678,0.001043061,0.001147785,0.0005831045,0.0009103488,0.003041005,0.001869154,0.003082369],"category_scores_gemma":[0.002813688,0.000560834,0.0008862249,0.001146518,0.0008132344,0.002310215,0.001541866,0.002172356,0.001027241],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001169471,"about_ca_system_score_gemma":0.001150244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007869897,"about_ca_topic_score_gemma":0.01340503,"domain_scores_codex":[0.9995205,0.00009499917,0.00001823756,0.0001705311,0.0001259148,0.0000698149],"domain_scores_gemma":[0.9990727,0.0003744293,0.00009391156,0.0001522772,0.000233263,0.00007326902],"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":[0.000769857,0.0004141008,0.004863779,0.0002058295,0.0002684981,0.0002686597,0.000152748,0.2549171,0.01229727,0.01480496,0.02390842,0.6871288],"study_design_scores_gemma":[0.00001249237,0.0000357573,0.0002675903,0.000009222764,0.00001671115,0.00003144539,0.000009082869,0.9878833,0.001712766,0.008785312,0.001228918,0.00000743337],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0412133,0.0009571273,0.9465067,0.0006552059,0.0002646664,0.000145237,0.0008226203,0.004254351,0.005180664],"genre_scores_gemma":[0.598963,0.0007911357,0.3818657,0.0009519053,0.0002829267,0.0003792594,0.00350069,0.000422823,0.01284259],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007869897,"threshold_uncertainty_score":0.01564819,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08308838273271177,"score_gpt":0.2197734280476417,"score_spread":0.1366850453149299,"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."}}