{"id":"W252500959","doi":"10.1007/978-3-642-35139-6_28","title":"A Preliminary Study Using Granular Computing for Remote Sensing Image Segmentation Involving Roughness","year":2012,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Granular computing; Computer science; Image segmentation; Segmentation; Image processing; Artificial intelligence; Computer vision; Image (mathematics); Rough set","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00198299,0.0007013108,0.0007256133,0.0007660358,0.0008360859,0.001000393,0.002038771,0.0002762509,0.000002525824],"category_scores_gemma":[0.00007876503,0.000663208,0.0001869977,0.0006563052,0.0003616478,0.001229244,0.001720129,0.0006481879,0.000006948047],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005024091,"about_ca_system_score_gemma":0.0003038984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001064458,"about_ca_topic_score_gemma":0.00003131404,"domain_scores_codex":[0.9953099,0.0001025666,0.0007958965,0.001760607,0.0009879976,0.001043066],"domain_scores_gemma":[0.9969284,0.0006266264,0.0005855144,0.001296217,0.0003738186,0.0001894237],"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":[0.00001764959,0.00005865431,0.0001052845,0.0001045098,0.00001850975,0.00009648527,0.005152402,0.02271102,0.0005308777,0.0003696273,0.000003292644,0.9708317],"study_design_scores_gemma":[0.0005303873,0.0003832996,0.0002020833,0.0004435187,0.00004021749,0.0001270789,0.00000550328,0.9690807,0.0004752913,0.02792266,0.00003067163,0.0007585327],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003508818,0.0008283143,0.9912998,0.0001036497,0.002148835,0.001746472,0.00000404999,0.0002027275,0.0001573361],"genre_scores_gemma":[0.1823343,0.000009636839,0.8165023,0.0003869219,0.0006971352,0.000001188664,0.000007348369,0.00005131901,0.000009790057],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9700732,"threshold_uncertainty_score":0.9995819,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03683949747874718,"score_gpt":0.2868925107239794,"score_spread":0.2500530132452322,"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."}}