{"id":"W2942793218","doi":"10.29173/bluejay20","title":"Saskatchewan Breeding Bird Atlas: 2017 Season Highlights","year":2018,"lang":"en","type":"article","venue":"Blue Jay","topic":"Arctic and Russian Policy Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Atlas (anatomy); Seasonal breeder; Geography; Fishery; Cartography; Ecology; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0008192827,0.0007723567,0.0004848429,0.002785954,0.001767983,0.001548614,0.0008390205,0.0005494092,0.05691265],"category_scores_gemma":[0.001263592,0.0004449827,0.0004254622,0.005812325,0.0003299438,0.0009382841,0.001487772,0.00115408,0.01392926],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006915782,"about_ca_system_score_gemma":0.02817417,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8488063,"about_ca_topic_score_gemma":0.9648438,"domain_scores_codex":[0.9996407,0.00003604816,0.00003413454,0.00005309415,0.0001242499,0.000111714],"domain_scores_gemma":[0.9971661,0.0001211834,0.00017057,0.0001626998,0.001925458,0.0004539152],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00009987369,0.0000230995,0.01292925,0.0001550838,0.00003226837,0.00005140856,0.00008432824,0.0001386095,0.0004264927,0.0004551878,0.9612119,0.02439249],"study_design_scores_gemma":[0.0000431615,0.0000130022,0.1636876,0.0002867707,0.00003173371,0.00007154938,0.0009283728,0.0002192251,0.0003034611,0.0004699695,0.8339069,0.00003820001],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.03959405,0.002868072,0.001922066,0.01196089,0.004469548,0.0006606235,0.6867764,0.001371356,0.2503771],"genre_scores_gemma":[0.08830854,0.00891724,0.008504806,0.008561146,0.0008566471,0.001914734,0.4059977,0.0009103598,0.4760289],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1511937,"threshold_uncertainty_score":0.3041682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03336944193635163,"score_gpt":0.3171008831499089,"score_spread":0.2837314412135573,"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."}}