{"id":"W2184384230","doi":"","title":"Transductive Learning of Structural SVMs via Prior Knowledge Constraints","year":2012,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Support vector machine; Artificial intelligence; Machine learning; Labeled data; Segmentation; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001922347,0.00008218124,0.000124187,0.00004768362,0.00005431867,0.00001518653,0.0003128489,0.00003955773,0.0001449363],"category_scores_gemma":[0.00001971938,0.00006861769,0.00004610305,0.0001137622,0.00007518021,0.0004340789,0.00007430289,0.0001231151,0.00002672504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001945661,"about_ca_system_score_gemma":0.00003365764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001456288,"about_ca_topic_score_gemma":0.000002030669,"domain_scores_codex":[0.9992644,0.00005245205,0.0001694042,0.0001596521,0.000112749,0.0002413345],"domain_scores_gemma":[0.9995671,0.00005230464,0.00004943052,0.0001945891,0.00005783287,0.00007873863],"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":[0.000003581187,0.00004076652,0.01031964,0.00003292453,0.00003275582,8.749237e-7,0.02150173,0.0003029461,0.01197111,0.2284403,0.00001466024,0.7273387],"study_design_scores_gemma":[0.001503599,0.0001860289,0.06090952,0.00006516865,0.00003130509,0.000151979,0.001279799,0.8288049,0.09743179,0.007257616,0.001526063,0.0008522881],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2261346,0.0001286089,0.7638282,0.00004758559,0.0003180133,0.0000657757,2.143086e-7,0.0000698866,0.009407115],"genre_scores_gemma":[0.9274566,6.857225e-7,0.07213299,0.0000147023,0.00007345575,0.000001586132,2.815796e-7,0.000003830562,0.0003159],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8285019,"threshold_uncertainty_score":0.2798148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02191180828113038,"score_gpt":0.2701434936984218,"score_spread":0.2482316854172914,"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."}}