{"id":"W2951601895","doi":"10.1139/facets-2018-0011","title":"Estimating the annual distribution of monarch butterflies in Canada over 16 years using citizen science data","year":2019,"lang":"en","type":"article","venue":"FACETS","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Espace pour la vie; University of Guelph","funders":"U.S. Fish and Wildlife Service; National Aeronautics and Space Administration","keywords":"Danaus; Geography; Citizen science; Distribution (mathematics); Habitat; Context (archaeology); Monarch butterfly; Ecology; Abundance (ecology); Biology; Archaeology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0005210156,0.0002687779,0.0001960785,0.00204934,0.0009663763,0.0007362671,0.0004922595,0.0002610621,0.000761406],"category_scores_gemma":[0.001627743,0.0002187946,0.000368693,0.002806073,0.0003137157,0.0003764246,0.0005585864,0.0003260995,0.0001670249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0106111,"about_ca_system_score_gemma":0.0111834,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.990103,"about_ca_topic_score_gemma":0.9962442,"domain_scores_codex":[0.9996791,0.00001932488,0.00002120093,0.00007767174,0.0001046133,0.00009802835],"domain_scores_gemma":[0.9985606,0.0001491833,0.0002395111,0.00007010617,0.0008098613,0.0001708261],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004062891,0.00001851347,0.9817278,0.00002865323,0.0000936662,0.00006198184,0.0003912882,0.00219359,0.0004182463,0.0001612734,0.002254546,0.01260978],"study_design_scores_gemma":[0.000003232291,0.000007809701,0.9908426,0.00002180335,0.00002649416,0.00003221836,0.0007778297,0.004867008,0.0001964785,0.00005013268,0.003161206,0.00001332363],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.983051,0.0002911689,0.0007321679,0.000185352,0.000005070086,0.00001848575,0.01431645,0.00005198804,0.001348425],"genre_scores_gemma":[0.9844774,0.0003436703,0.001559268,0.00006124346,0.000003776097,0.00001934997,0.01217883,0.000009714902,0.001346704],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0106111,"threshold_uncertainty_score":0.07698929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03377011217132955,"score_gpt":0.2743176045543184,"score_spread":0.2405474923829889,"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."}}