{"id":"W2143482925","doi":"","title":"Constrained classification on structured data","year":2008,"lang":"en","type":"article","venue":"Journal of Bioresource Management","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Cancer Foundation; University of Alberta","funders":"","keywords":"Conditional random field; Random forest; Independent and identically distributed random variables; Support vector machine; Computer science; Artificial intelligence; Random field; Pixel; Pattern recognition (psychology); Segmentation; Field (mathematics); Machine learning; Image segmentation; Random variable; Mathematics; Statistics","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":[0.0003405362,0.0001053634,0.0001506102,0.0002245064,0.0000959744,0.00005155713,0.001566789,0.00003164558,0.000008818871],"category_scores_gemma":[0.00003575324,0.00008141542,0.00005348566,0.0002891558,0.00007152871,0.0003896029,0.0003390622,0.0001528228,0.000008983162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004487329,"about_ca_system_score_gemma":0.00002069952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.015224e-7,"about_ca_topic_score_gemma":1.039818e-7,"domain_scores_codex":[0.9988065,0.00004394621,0.0003520074,0.0002177137,0.0004349997,0.0001448836],"domain_scores_gemma":[0.9986011,0.00003744195,0.0003627402,0.0008393315,0.00008458154,0.00007483119],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009526755,0.0001959911,0.0004218156,0.00003021969,0.0001331939,0.0007904147,0.0002976558,0.00009804817,0.001814724,0.03067685,0.03872804,0.9267178],"study_design_scores_gemma":[0.003521825,0.002545095,0.09795673,0.0003371327,0.0001167649,0.001432452,0.0004119799,0.03131459,0.02570486,0.01121386,0.8244925,0.0009522502],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005327658,0.0001027566,0.9899792,0.0009345151,0.000148138,0.0001327002,0.000003235346,0.00006651135,0.003305303],"genre_scores_gemma":[0.7185797,0.0003567224,0.279977,0.0006487863,0.0001773379,0.000001127744,0.000003996505,0.000008757156,0.0002465302],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9257655,"threshold_uncertainty_score":0.3320024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0741648183093897,"score_gpt":0.3045203509877292,"score_spread":0.2303555326783395,"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."}}