{"id":"W6977039553","doi":"10.6084/m9.figshare.25769157","title":"Data from \"Estimating rapid diversity changes during acute herbicide contamination using environmental DNA\"","year":2024,"lang":"en","type":"dataset","venue":"Figshare","topic":"Economic and Social Issues","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Table (database); Sampling (signal processing); Raw data; Mesocosm; Diversity (politics); Contamination","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":["insufficient_payload"],"category_scores_codex":[0.0001343247,0.0002073691,0.0002855571,0.00006371018,0.001204262,0.0002426199,0.001017593,0.0003426878,0.1676728],"category_scores_gemma":[0.0002835524,0.0002484346,0.00005969119,0.00006137281,0.00004270839,0.0004199057,0.002460681,0.0002990514,0.007887878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004616818,"about_ca_system_score_gemma":0.0000821806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004567536,"about_ca_topic_score_gemma":0.009924185,"domain_scores_codex":[0.9986159,0.0001145682,0.0001687404,0.0005318875,0.0002809949,0.0002878976],"domain_scores_gemma":[0.9990965,0.000156553,0.0002249757,0.0004145476,0.00001165879,0.00009575038],"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":[0.00000233511,0.00001018905,0.00001305308,0.00007660904,0.0001016156,0.00005174185,0.001977973,6.774699e-7,0.000007034556,3.174809e-7,0.9974834,0.0002750136],"study_design_scores_gemma":[0.00009263956,0.000006299915,0.0001971167,0.001138967,0.0001687338,5.320156e-7,0.001801616,0.0002062414,0.00001476134,0.00002329304,0.9960513,0.0002985316],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001898103,0.0007280339,1.280221e-7,0.00007508458,0.0004976689,0.000253367,0.9962751,0.00006500317,0.0002075173],"genre_scores_gemma":[0.000885216,0.0001347243,0.00006803536,0.00006997962,0.002029168,0.0000136535,0.9965184,0.0000178218,0.0002630563],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1597849,"threshold_uncertainty_score":0.9999968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1280092683379457,"score_gpt":0.3338257867805269,"score_spread":0.2058165184425813,"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."}}