{"id":"W2999580921","doi":"","title":"Mapping boreal forest deciduous fractional cover across Alaska and Western Canada","year":2018,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Deciduous; Taiga; Boreal; Geography; Forestry; Physical geography; Cover (algebra); Snow cover; Forest cover; Environmental science; Climatology; Ecology; Geology; Meteorology; Archaeology; Snow; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002830462,0.0001591296,0.0001510874,0.0000279888,0.0003861958,0.0001421293,0.0001301945,0.00008128665,0.0001159009],"category_scores_gemma":[0.00008787049,0.0001445018,0.00002416886,0.00008698248,0.000105616,0.0002008671,0.00002328719,0.0001564195,0.0001833843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001744573,"about_ca_system_score_gemma":0.0001451675,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9681012,"about_ca_topic_score_gemma":0.9990728,"domain_scores_codex":[0.9986707,0.00002347974,0.0002422054,0.0002849171,0.0002983216,0.0004803948],"domain_scores_gemma":[0.9991357,0.000334637,0.0001237538,0.0001300786,0.00006777295,0.0002080378],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001848449,0.000004728134,0.9933502,0.00001499635,0.00001104764,0.00005842914,0.0005457393,0.0004621833,0.00001988423,2.438034e-7,0.002958786,0.002555245],"study_design_scores_gemma":[0.0001930116,0.00004500868,0.9667913,0.00005524532,0.000004695917,0.00008074632,0.0004542428,0.0006890263,0.0000341242,0.00002409851,0.03144694,0.0001815541],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9800898,0.000171539,0.000003213497,0.0002871124,0.0005870234,0.0000765763,0.000696426,0.00002850994,0.01805979],"genre_scores_gemma":[0.9971221,0.00005030581,0.00006305314,0.001073241,0.0007754584,7.959952e-7,0.0006738388,0.000006687069,0.000234489],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0309717,"threshold_uncertainty_score":0.5892613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02748716806035299,"score_gpt":0.2468054470255984,"score_spread":0.2193182789652454,"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."}}