{"id":"W4393835114","doi":"10.5281/zenodo.1492618","title":"Covariate layers (30 m) for soil mapping Canada --- ALOS AW3D30, tree cover","year":2018,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cover (algebra); Covariate; Forestry; Tree (set theory); Environmental science; Physical geography; Geography; Mathematics; Statistics; Combinatorics; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007468499,0.00207947,0.001258284,0.002610825,0.001086103,0.001983479,0.003100915,0.001267388,0.04804816],"category_scores_gemma":[0.003491566,0.0008056625,0.00131284,0.007716957,0.000493918,0.0008355153,0.001454679,0.001859987,0.04677603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00381987,"about_ca_system_score_gemma":0.01114551,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6132824,"about_ca_topic_score_gemma":0.7922151,"domain_scores_codex":[0.9992716,0.00006584542,0.00006294337,0.0002287567,0.0002071016,0.000163823],"domain_scores_gemma":[0.9982053,0.0001771443,0.0001383313,0.000368184,0.0008951498,0.0002159241],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005110037,0.00001377723,0.001726691,0.0003053344,0.00004826137,0.00001697309,0.00002999873,0.0005839392,0.0001015132,0.000411816,0.9944289,0.002281675],"study_design_scores_gemma":[0.0003130717,0.000008476387,0.01090799,0.0002407879,0.00005842753,0.00004430099,0.0001015163,0.001012754,0.0004744834,0.00107018,0.9857255,0.00004250393],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001394345,0.00003180623,0.0001011464,0.00002166429,0.000007049193,0.000006925281,0.9990736,0.0003269696,0.000291485],"genre_scores_gemma":[0.0004841848,0.00003126074,0.0004154189,0.00001509959,0.000002341264,0.00004964131,0.9983871,0.000104949,0.0005101382],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3867176,"threshold_uncertainty_score":0.77799,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03194042987265625,"score_gpt":0.2274932278572476,"score_spread":0.1955527979845913,"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."}}