{"id":"W2982170513","doi":"10.4095/220024","title":"Accuracy assessment of global land cover products derived from satellite data","year":2003,"lang":"en","type":"report","venue":"","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Land cover; Satellite; Cover (algebra); Remote sensing; Environmental science; Geography; Land use; Biology; Ecology; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007563567,0.0005431797,0.0003721733,0.00376847,0.0003092937,0.001349908,0.0006038346,0.0005459566,0.001143335],"category_scores_gemma":[0.02226118,0.0001725755,0.0006072102,0.002962718,0.0004220411,0.001002453,0.0006911313,0.0003039808,0.0006597359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00132637,"about_ca_system_score_gemma":0.000796003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01920399,"about_ca_topic_score_gemma":0.0181828,"domain_scores_codex":[0.9937317,0.001175596,0.0005000736,0.0003985676,0.003976342,0.0002177874],"domain_scores_gemma":[0.9811862,0.006957797,0.001326463,0.001775952,0.008641439,0.0001120515],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004107484,0.000153996,0.4893733,0.0005821891,0.0003508746,0.0002991725,0.0006150165,0.07582223,0.01046093,0.002984087,0.01016155,0.4087859],"study_design_scores_gemma":[0.00005903872,0.0004485259,0.811121,0.0003304935,0.0003765453,0.0005357471,0.0008085094,0.1197948,0.03758731,0.003307898,0.02552892,0.0001010397],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8293751,0.006413716,0.09910925,0.001015821,0.0001886769,0.0005479563,0.0224358,0.00165766,0.03925605],"genre_scores_gemma":[0.9165472,0.001927673,0.0547707,0.00009446472,0.00009573962,0.0001571048,0.02234864,0.0001966429,0.003861821],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01920399,"threshold_uncertainty_score":0.04000044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07533219262385672,"score_gpt":0.3201229228635264,"score_spread":0.2447907302396697,"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."}}