{"id":"W4221036183","doi":"10.14430/arctic74868","title":"Improving Peary Caribou Presence Predictions in MaxEnt Using Spatialized Snow Simulations","year":2022,"lang":"en","type":"article","venue":"ARCTIC","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; Université Laval; Université de Sherbrooke; Natural Sciences and Engineering Research Council of Canada","funders":"Natural Sciences and Engineering Research Council of Canada; Institut National de Recherche en Sciences et Technologies pour l'Environnement et l'Agriculture; Environment and Climate Change Canada; Government of Nunavut; Polar Knowledge Canada","keywords":"Snow; Snowpack; Arctic; Environmental science; Climatology; Forage; Physical geography; Snow field; Winter storm; Atmospheric sciences; Geography; Ecology; Meteorology; Geology; Oceanography; Snow cover; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0007373379,0.00078672,0.0006496391,0.0006501687,0.0007800622,0.001008667,0.001408526,0.000961773,0.001593799],"category_scores_gemma":[0.002415334,0.0006425949,0.001020251,0.0005508507,0.0004665769,0.0006491891,0.000671139,0.0005862452,0.0001808899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001817112,"about_ca_system_score_gemma":0.002864979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3323148,"about_ca_topic_score_gemma":0.2901621,"domain_scores_codex":[0.9998401,0.00004846525,0.000009436941,0.00003632951,0.00002567615,0.00004003407],"domain_scores_gemma":[0.9990802,0.0004817584,0.00007402092,0.00005137558,0.0001938362,0.0001187243],"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":[0.00006202215,0.00003902283,0.009780494,0.00001592444,0.0000410027,0.00003426479,0.00004083731,0.9877511,0.0003126023,0.0002715374,0.0002326894,0.001418537],"study_design_scores_gemma":[0.00001259256,0.000009083527,0.0009772169,0.000003097641,0.000007329497,0.000003034284,0.00001757155,0.9986534,0.00009830525,0.00007030412,0.0001433602,0.000004751879],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9823669,0.0001339503,0.01142332,0.000231232,0.00003740582,0.00003735092,0.001100492,0.0006119724,0.004057395],"genre_scores_gemma":[0.9897434,0.00005827813,0.008466897,0.00005008977,0.00001336308,0.00003114954,0.0009423656,0.0000712954,0.0006231211],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3323148,"threshold_uncertainty_score":0.6607609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03069380969810778,"score_gpt":0.2364138479265568,"score_spread":0.2057200382284491,"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."}}