{"id":"W2745270433","doi":"","title":"Adapting hydrological modeling for Atlantic Canada's climate, landscape, and vegetation conditions","year":2017,"lang":"en","type":"article","venue":"","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Vegetation (pathology); Environmental science; Climate change; Geography; Environmental resource management; Climatology; Physical geography; Geology; Oceanography","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":[0.0005398783,0.0003902642,0.0003564339,0.0005328689,0.001382377,0.001428577,0.001603746,0.0007763259,0.002536836],"category_scores_gemma":[0.002494691,0.0003753203,0.0006563503,0.001083388,0.0003550769,0.000630716,0.0005567945,0.0008577687,0.0002055175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01239802,"about_ca_system_score_gemma":0.01968539,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9737231,"about_ca_topic_score_gemma":0.9792821,"domain_scores_codex":[0.9997624,0.00004558395,0.0000126064,0.00006165232,0.00005138263,0.00006636848],"domain_scores_gemma":[0.9992792,0.0001570494,0.00003923326,0.000053582,0.0003678971,0.0001031266],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003500235,0.00006812285,0.02062238,0.00001770173,0.00007406261,0.00004976503,0.00008968458,0.9631522,0.0006439186,0.001762861,0.002570051,0.01091421],"study_design_scores_gemma":[0.00002362263,0.00000520351,0.006448612,0.000004888865,0.00002612063,0.000007094011,0.00009678676,0.9909184,0.0001878362,0.0005505753,0.001712946,0.00001791014],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9408885,0.0001974807,0.02846983,0.00237156,0.0002083152,0.0001478504,0.004934987,0.001526601,0.02125489],"genre_scores_gemma":[0.9849772,0.0001208028,0.01134373,0.0001401562,0.00002551348,0.00003666185,0.001027513,0.0001475165,0.002180872],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02627689,"threshold_uncertainty_score":0.08995438,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05505267287252856,"score_gpt":0.2604303244913417,"score_spread":0.2053776516188132,"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."}}