{"id":"W2158065679","doi":"10.1080/01431160701281064","title":"Evaluation of segment‐based gap‐filled Landsat ETM+ SLC‐off satellite data for land cover classification in southern Saskatchewan, Canada","year":2008,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Statistics Canada; Agricultural Institute of Canada","funders":"U.S. Geological Survey","keywords":"Thematic Mapper; Land cover; Remote sensing; Contextual image classification; Thematic map; Satellite; Decision tree; Satellite imagery; Geography; Cartography; Land use; Computer science; Data mining; Image (mathematics); Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00162999,0.00009001795,0.0001660287,0.0001067126,0.00003822274,0.00002960863,0.0005892537,0.00004877161,0.00000802848],"category_scores_gemma":[0.0005310722,0.00008171397,0.00004660053,0.0001107666,0.00002455541,0.0001887023,0.00007515569,0.0001173285,8.034168e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002165093,"about_ca_system_score_gemma":0.001224318,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.009069274,"about_ca_topic_score_gemma":0.05562302,"domain_scores_codex":[0.9981155,0.0001145773,0.0004747531,0.0001836685,0.000989538,0.0001219918],"domain_scores_gemma":[0.9972582,0.0001927229,0.0005623267,0.0002860894,0.001658296,0.00004232148],"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":[0.0003491983,0.0001043412,0.006691538,0.00005139849,0.0003074026,0.0002080538,0.003217337,0.07221698,0.03438203,0.00002131717,0.001966958,0.8804834],"study_design_scores_gemma":[0.001622056,0.00002143178,0.002254812,0.0001557738,0.00002420186,0.00020112,0.000343382,0.9839512,0.004207108,0.0005311873,0.006587507,0.0001002757],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6551621,0.0003679195,0.3351097,0.006579364,0.001008996,0.0002407267,0.00005192468,0.00001196004,0.001467305],"genre_scores_gemma":[0.9682898,0.00001798233,0.03120889,0.0001539022,0.0001387923,5.474807e-8,0.00005055331,0.000003010158,0.0001370133],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9117342,"threshold_uncertainty_score":0.9975294,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08175275359171674,"score_gpt":0.2944674763665058,"score_spread":0.2127147227747891,"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."}}