{"id":"W3165855571","doi":"10.1109/isbi48211.2021.9434036","title":"Colorectal Cancer Tissue Classification Using Semi-Supervised Hypergraph Convolutional Network","year":2021,"lang":"en","type":"article","venue":"","topic":"AI in cancer detection","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Terry Fox Foundation","keywords":"Hypergraph; Artificial intelligence; Computer science; Convolutional neural network; Pattern recognition (psychology); Deep learning; Artificial neural network; Mathematics","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":[0.0004807152,0.0008187606,0.000648817,0.001349536,0.0003533468,0.0006314056,0.001438023,0.0009832316,0.001051529],"category_scores_gemma":[0.000872913,0.0003494841,0.0008371758,0.0006939922,0.0005135725,0.0008861505,0.0007417703,0.0006629034,0.0004419888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001060248,"about_ca_system_score_gemma":0.0009119766,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01298974,"about_ca_topic_score_gemma":0.0198826,"domain_scores_codex":[0.9996219,0.00006871184,0.00002103217,0.0001432916,0.00008354789,0.00006162708],"domain_scores_gemma":[0.999504,0.000139538,0.00008633221,0.00008951244,0.0001399966,0.00004056107],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005538811,0.0004469361,0.009494924,0.0001427633,0.0002477818,0.000302988,0.000157897,0.5087398,0.02349613,0.002818392,0.006170172,0.4474283],"study_design_scores_gemma":[0.000005029419,0.00002142355,0.0007289025,0.00000395019,0.0000102261,0.00002936978,0.000007148574,0.9965108,0.00165004,0.0008252257,0.0002026476,0.000005312176],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2444589,0.0008677431,0.7437822,0.0004854349,0.00008217597,0.0002093422,0.0007817895,0.006113373,0.003219017],"genre_scores_gemma":[0.8858664,0.0002769532,0.1063314,0.0002771789,0.00004845807,0.0001043832,0.001955163,0.0001057193,0.005034344],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01298974,"threshold_uncertainty_score":0.02582824,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03826354965499948,"score_gpt":0.2863943663856532,"score_spread":0.2481308167306538,"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."}}