{"id":"W3172591507","doi":"","title":"Unsupervised Part Representation by Flow Capsules","year":2021,"lang":"en","type":"article","venue":"International Conference on Machine Learning","topic":"Image Processing and 3D Reconstruction","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Representation (politics); Flow (mathematics); Artificial intelligence; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001398539,0.0001118827,0.0001035928,0.00007885713,0.0001646013,0.0004613699,0.0003700051,0.00004514034,0.0004835016],"category_scores_gemma":[0.0002184119,0.0001113349,0.00004873075,0.0001664488,0.00002999653,0.0004528899,0.00009972064,0.0003114814,0.0001071993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003335243,"about_ca_system_score_gemma":0.0001116388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003863666,"about_ca_topic_score_gemma":0.00000888807,"domain_scores_codex":[0.9988105,0.0001319524,0.0001915768,0.0003871275,0.0003368676,0.0001420292],"domain_scores_gemma":[0.9993001,0.00005060681,0.00009886746,0.000176144,0.000323434,0.00005087761],"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":[0.00002606641,0.0001305429,0.007905451,0.00001644219,0.00007882997,0.00007041002,0.0008271751,0.003701667,0.0305307,0.0571544,0.002652952,0.8969054],"study_design_scores_gemma":[0.000422605,0.00003439992,0.000347811,0.00006855468,0.000003862847,0.00007900086,0.0001085974,0.9626545,0.01835328,0.003817456,0.01392841,0.0001815634],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04230724,0.0003943992,0.840976,0.0176376,0.003110096,0.00009974461,0.00002344025,0.0005549374,0.09489654],"genre_scores_gemma":[0.9679893,0.0001348122,0.02183018,0.0004401169,0.0001666151,0.00001121969,0.0002189017,0.00001090412,0.009197914],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9589528,"threshold_uncertainty_score":0.5294004,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03204435531729514,"score_gpt":0.2907227342666551,"score_spread":0.2586783789493599,"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."}}