{"id":"W2741752675","doi":"10.24963/ijcai.2017/481","title":"Multi-Instance Learning with Key Instance Shift","year":2017,"lang":"en","type":"article","venue":"","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Novelis (Canada)","funders":"National Natural Science Foundation of China","keywords":"Key (lock); Computer science; Embedding; Artificial intelligence; Class (philosophy); Machine learning; Test (biology); Computer security","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":[0.003594426,0.0017073,0.002851948,0.001842695,0.0007282753,0.002150953,0.004266891,0.002741524,0.002077296],"category_scores_gemma":[0.01220122,0.0008205488,0.001762503,0.002506203,0.001245529,0.005234045,0.003688519,0.004681272,0.001114017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001196266,"about_ca_system_score_gemma":0.0009947233,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00137032,"about_ca_topic_score_gemma":0.001409821,"domain_scores_codex":[0.9966,0.001098173,0.0002547296,0.001207381,0.0005835391,0.0002562561],"domain_scores_gemma":[0.9953311,0.002203293,0.0004178543,0.001249268,0.0005634322,0.0002349064],"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":[0.0006134755,0.0005896524,0.004367277,0.000325105,0.0003179722,0.0002355422,0.0002553027,0.2629299,0.006105397,0.01693232,0.009717842,0.6976102],"study_design_scores_gemma":[0.00003008579,0.00007239388,0.0002121111,0.0000100296,0.00002634734,0.00006830278,0.00002583231,0.9776985,0.002463706,0.01851756,0.0008598565,0.00001529169],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02106122,0.000653811,0.974851,0.0003432034,0.00008430245,0.0001259401,0.0001890928,0.001933631,0.0007578639],"genre_scores_gemma":[0.5474126,0.0003865489,0.4468157,0.0008001185,0.0002284286,0.0003425327,0.00192475,0.000306086,0.001783254],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004266891,"threshold_uncertainty_score":0.01900935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02581297414061309,"score_gpt":0.2730585649282863,"score_spread":0.2472455907876732,"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."}}