{"id":"W2487092032","doi":"10.1142/9789814273398_0007","title":"A REGION TREE BASED IMAGE DISCRETE LABELING FRAMEWORK","year":2009,"lang":"en","type":"book-chapter","venue":"WORLD SCIENTIFIC eBooks","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Tree (set theory); Image (mathematics); Computer science; Artificial intelligence; Computer vision; Mathematics; Combinatorics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007126993,0.0007054788,0.001241733,0.001394091,0.0006524682,0.00189931,0.003126991,0.001065992,0.004436907],"category_scores_gemma":[0.0009947508,0.0006415051,0.001172239,0.002287037,0.0007654079,0.002395969,0.00165041,0.00177459,0.002115557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001025016,"about_ca_system_score_gemma":0.0009857842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008349037,"about_ca_topic_score_gemma":0.009710663,"domain_scores_codex":[0.9994363,0.00009147459,0.00002200287,0.0001648807,0.0002315194,0.00005378668],"domain_scores_gemma":[0.999524,0.0001246005,0.0000313583,0.0001362353,0.000146192,0.00003766539],"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":[0.0001812656,0.000169384,0.0003850831,0.0002734271,0.00007549256,0.0001552682,0.0001938583,0.1969741,0.02318247,0.1469135,0.01147227,0.620024],"study_design_scores_gemma":[0.00001048022,0.00003169521,0.0001198852,0.00001852571,0.00002236409,0.00009266626,0.00002494619,0.9420109,0.005377414,0.04272506,0.009547734,0.00001834669],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0009567832,0.0001204183,0.9974054,0.00002914981,0.00001206871,0.00001780703,0.0001107976,0.0006740191,0.0006736904],"genre_scores_gemma":[0.0404987,0.0003529314,0.9545599,0.00006615448,0.00003738274,0.00008000228,0.0008026207,0.0003918094,0.003210645],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008349037,"threshold_uncertainty_score":0.01660085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01738222950410967,"score_gpt":0.2355614008130283,"score_spread":0.2181791713089186,"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."}}