{"id":"W6911134786","doi":"10.5066/p961r9pj","title":"GRTS for Integrated Monarch Monitoring Program Code","year":2018,"lang":"en","type":"dataset","venue":"USGS DOI Tool Production Environment","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Code (set theory); Scripting language; Source code; Stratified sampling; Sampling (signal processing); Data file","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001345308,0.001124791,0.0007953079,0.000493305,0.0004988417,0.0001944055,0.0008150926,0.0006770565,0.0006922971],"category_scores_gemma":[0.0004058623,0.001103728,0.0003167352,0.0003528027,0.0006052117,0.0003829051,0.000362965,0.0009903328,0.00802452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002131897,"about_ca_system_score_gemma":0.0001241014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001180131,"about_ca_topic_score_gemma":0.00001184789,"domain_scores_codex":[0.9936645,0.0002442781,0.001058294,0.002540102,0.001340538,0.001152289],"domain_scores_gemma":[0.9961159,0.00005670091,0.0008057185,0.002654597,0.0001335644,0.0002334878],"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":[0.0003348348,0.001525827,0.00008435008,0.0002873988,0.0002900491,0.000007265248,0.00005885059,0.0005481174,0.001948411,9.161769e-7,0.9849303,0.009983642],"study_design_scores_gemma":[0.0005992663,0.0007864199,0.0003822781,0.0001912041,0.0004276022,0.00004912408,0.0000649932,0.00005577449,0.006145845,0.00005100468,0.9901231,0.001123375],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003928286,0.0002971014,0.00007932332,0.0002455791,0.004632684,0.007819557,0.9824398,0.0005469929,0.00001070757],"genre_scores_gemma":[0.0001544018,0.0006246234,0.01035545,0.00001674553,0.007018073,0.007163193,0.9716495,0.0003515757,0.002666414],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01079024,"threshold_uncertainty_score":0.9991413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03576053502726664,"score_gpt":0.3021960493287794,"score_spread":0.2664355143015128,"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."}}