{"id":"W7131066419","doi":"10.1109/iccvw69036.2025.00077","title":"HAPPI: Hyperbolic Hierarchical Part Prototypes for Image Recognition","year":2025,"lang":"","type":"article","venue":"","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Discriminative model; Hierarchy; Aggregate (composite); Euclidean geometry; Image (mathematics); Feature (linguistics); Key (lock); Convolutional neural network; Pattern recognition (psychology)","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":[0.000989683,0.001269128,0.001012891,0.001324273,0.0004403779,0.001671317,0.003927858,0.001771983,0.008454761],"category_scores_gemma":[0.00301428,0.0009524898,0.001287343,0.001190982,0.0008070486,0.002842915,0.002202917,0.001940849,0.003791603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001276178,"about_ca_system_score_gemma":0.0009560302,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003885521,"about_ca_topic_score_gemma":0.006663844,"domain_scores_codex":[0.9993753,0.00008712848,0.00002852127,0.0002492801,0.0001841171,0.00007577611],"domain_scores_gemma":[0.9994042,0.0001441584,0.00007149806,0.0002115928,0.0001081498,0.00006041924],"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":[0.0005650842,0.0001364549,0.001460851,0.0003958783,0.0001673573,0.0001840267,0.0002448279,0.1130637,0.03162227,0.02370992,0.03218618,0.7962633],"study_design_scores_gemma":[0.00003598067,0.0001400124,0.000574666,0.00003722633,0.00002471955,0.0002166891,0.00005418208,0.9496349,0.0148401,0.02489037,0.009516234,0.00003495737],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01307094,0.0006289326,0.9666829,0.0002178237,0.0001142503,0.0001925661,0.00110243,0.01531907,0.002671039],"genre_scores_gemma":[0.1980085,0.0004921778,0.7877228,0.0003840875,0.0000802397,0.0004241835,0.004347739,0.001163042,0.007377347],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008454761,"threshold_uncertainty_score":0.02828401,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03243677614771632,"score_gpt":0.3277537902724389,"score_spread":0.2953170141247226,"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."}}