{"id":"W2134282875","doi":"10.1145/1390156.1390163","title":"Multiple instance ranking","year":2008,"lang":"en","type":"article","venue":"","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies; Rensselaer Polytechnic Institute","keywords":"Computer science; Ranking (information retrieval); Artificial intelligence; Information retrieval","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006366675,0.00004306248,0.00004810746,0.00003123343,0.0001063029,0.00002333122,0.0003631971,0.0000194033,0.00001654408],"category_scores_gemma":[0.0000264335,0.00003501364,0.0000240691,0.0002300786,0.00002894919,0.0003151159,0.00005628958,0.00004202388,0.00007752047],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001291157,"about_ca_system_score_gemma":0.00002261632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007149509,"about_ca_topic_score_gemma":9.072293e-7,"domain_scores_codex":[0.9995474,0.00001138029,0.00008424155,0.0001379029,0.0001226174,0.00009644128],"domain_scores_gemma":[0.9996223,0.00002855797,0.00002383228,0.0002524676,0.00004639492,0.00002641697],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00000946811,0.0001664183,0.01434681,0.00001361498,0.00001153823,0.00006388772,0.001236688,0.000001889372,0.05757329,0.6035294,0.01147035,0.3115767],"study_design_scores_gemma":[0.0004351886,0.00004476166,0.0194803,0.00001118373,9.402383e-7,0.00009631577,0.00001477413,0.05246348,0.7919366,0.005778451,0.1294232,0.0003147926],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002517015,0.00006415733,0.9741114,0.0004281243,0.00005099628,0.0000478062,1.210014e-7,0.0005569857,0.02222336],"genre_scores_gemma":[0.8606724,0.00004048468,0.1369186,0.000489508,0.00001402082,0.000005180837,2.498968e-7,0.000002061016,0.001857568],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8581553,"threshold_uncertainty_score":0.1427815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0312882596491182,"score_gpt":0.2318379867827939,"score_spread":0.2005497271336756,"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."}}