{"id":"W6892301473","doi":"10.5066/p9fatni9","title":"Greater sage-grouse genetic warning system, western United States (ver 1.1, January 2023)","year":2022,"lang":"en","type":"dataset","venue":"USGS DOI Tool Production Environment","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Population; Genetic diversity; Warning system; Proxy (statistics); Diversity (politics); Identification (biology); Early warning system; Population size","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.0005376501,0.0005538965,0.0002572773,0.00123748,0.0004841533,0.0008298944,0.0005549997,0.0004549684,0.09202702],"category_scores_gemma":[0.00160663,0.0003578419,0.0001455598,0.001364415,0.0001680221,0.000744336,0.0007047914,0.0006748806,0.03878504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006385038,"about_ca_system_score_gemma":0.001087042,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0698708,"about_ca_topic_score_gemma":0.1527169,"domain_scores_codex":[0.999772,0.00002526498,0.00002399995,0.00004697809,0.0001089802,0.00002291828],"domain_scores_gemma":[0.9988152,0.0001538016,0.0002001456,0.0001013123,0.0005380405,0.0001915169],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000169331,0.00007707326,0.01107375,0.0001294062,0.000009091766,0.00005175204,0.00009781768,0.0002110001,0.00081315,0.0004802623,0.924427,0.06246042],"study_design_scores_gemma":[0.0001133622,0.00008469602,0.09130844,0.0001872073,0.00001362508,0.00006724805,0.0001445804,0.001323182,0.0006370362,0.0005923219,0.9054931,0.00003528181],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.02119073,0.0006406903,0.005029783,0.001234029,0.0006962133,0.000884479,0.7677599,0.01123926,0.1913249],"genre_scores_gemma":[0.04444775,0.0009652841,0.02564298,0.001975759,0.0002457307,0.00217773,0.6941528,0.001773677,0.2286183],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09202702,"threshold_uncertainty_score":0.307861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01140700509319756,"score_gpt":0.1958965584459549,"score_spread":0.1844895533527574,"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."}}