{"id":"W2988289684","doi":"10.3390/rs11222627","title":"Purifying SLIC Superpixels to Optimize Superpixel-Based Classification of High Spatial Resolution Remote Sensing Image","year":2019,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"National Natural Science Foundation of China","keywords":"Computer science; Pattern recognition (psychology); Artificial intelligence; Cluster analysis; Pixel; Contextual image classification; Segmentation; Remote sensing; Image (mathematics)","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":[0.0007422153,0.0005631641,0.0007570026,0.0006975314,0.0001835749,0.0001789247,0.0002387175,0.0003879874,0.00002012685],"category_scores_gemma":[0.0004606168,0.0006641083,0.0002313959,0.0009283932,0.000129185,0.0003852965,0.0000729811,0.0005504515,0.0003238335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007331086,"about_ca_system_score_gemma":0.0001270001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008395325,"about_ca_topic_score_gemma":0.00007957402,"domain_scores_codex":[0.9962853,0.0002581502,0.001068681,0.0008508912,0.0007089362,0.0008280802],"domain_scores_gemma":[0.9971965,0.0003021357,0.0002406378,0.001462476,0.0005418783,0.0002563473],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006371891,0.000006668455,0.000004697129,0.0001675983,0.00002796476,0.00001238594,0.0002276637,0.06961613,0.7031281,0.000008132602,0.000107102,0.2266298],"study_design_scores_gemma":[0.0007039944,0.00005398169,0.001244088,0.000597437,0.0000587799,0.00005399451,0.0001188513,0.8191995,0.176756,0.0001138448,0.0005548932,0.0005445982],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4652118,0.00004325576,0.5311179,0.0004128747,0.0007888078,0.0005658399,0.000007181071,0.0004836949,0.001368645],"genre_scores_gemma":[0.6485409,0.00001618168,0.3508421,0.00007598878,0.0002245086,1.363468e-8,0.00006929647,0.0001575549,0.00007339919],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7495834,"threshold_uncertainty_score":0.999581,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01863949118982053,"score_gpt":0.2371231205228785,"score_spread":0.2184836293330579,"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."}}